Model · Anthropic
Claude Fable 5.1
Anthropic’s highest-priced Claude model in these studies, measured through Claude Code.
29 values from 6 studies (17 are list-price calculations) · Updated
At a glance
The best-supported value per category: a 95% interval first, then a run range, then the larger n. Three separate values from separate studies, never one score.
Qualitypass rates, accuracy and scores
100% (24/24)
95% CI 86%–100% · n = 24
Pass rate on eight hard tasks (Strict pass)
Claude Code · eight hard validated tasks · Haiku vs Sonnet vs Opus vs Fable vs GPT-6.1 Sol on 8 hard tasks
Speedtime per call or decision
16.1s
range 4.5 s–90 s · n = 24
Total time per call on hard tasks (separate batches)
Claude Code · eight hard validated tasks · Haiku vs Sonnet vs Opus vs Fable vs GPT-6.1 Sol on 8 hard tasks
CostUS dollars per call, pass or decision
$0.0099
range $0.0049–$0.058 · n = 15 · list-price calculation
List-price cost per call (calculation)
Claude Code · five short validated tasks · Haiku vs Sonnet vs Opus vs Fable vs Codex: a timed head-to-head
Claude Fable 5.1 price per 1M tokens
Claude Fable 5.1 costs $10.00 per 1M input tokens and $50.00 per 1M output tokens at standard Claude API list prices (observed 2026-10-08). Cache reads cost $0.25 per 1M tokens.
Vendor list price
$10.00
Input, per 1M tokens
Vendor list price
$50.00
Output, per 1M tokens
Vendor list price
$0.25
Cache read, per 1M tokens
Vendor specification · 2026-10-08
1M
Context window, tokens
Cache writes are separate: $12.50 per 1M tokens for five minutes; $20.00 per 1M tokens for one hour. Standard global Claude API prices; other tiers, tools and taxes can add charges.
Source: Official Claude API prices · observed .
Context: Official model specification · observed . Route and provider limits can be lower than the model specification.
Recorded study price source: Anthropic list prices (Claude models) (). Prices as listed by the vendor on 2026-09-21 and recorded in the product price table. Cache reads at the listed rate, one-hour cache writes at twice the input price.
Providers in the dated snapshot
4 standard-tier providers · snapshot 2026-10-06 · USD per 1M tokens
- Anthropicfirst-party
- Amazon Bedrock
- Azure
- Google Vertex
| Provider | Input $/1M | Output $/1M | Cache read $/1M | Reported endpoint context (tokens) | Uptime, last day |
|---|---|---|---|---|---|
| Anthropic (first-party) | $10.00 | $50.00 | $0.25 | 1,000,000 | 99.65% |
| Amazon Bedrock | $10.00 | $50.00 | $0.25 | 1,000,000 | not reported |
| Azure | $10.00 | $50.00 | $0.25 | 1,000,000 | 99.36% |
| Google Vertex | $10.00 | $50.00 | $0.25 | 1,000,000 | 99.92% |
Third-party-reported, not measured by Agent · Standard tier only: regional, flex, fast and priority tiers are left out · One row per provider: its cheapest standard endpoint
Claude Fable 5.1: 4 standard-tier providers, all at the same price ($10.00 input, $50.00 output per 1M tokens). Third-party-reported, snapshot 2026-10-06.
Source: OpenRouter public API: models and provider endpoints (snapshot) (). The diamond marks the first-party provider in this snapshot. Current availability is not checked.
Estimate your monthly costPrices of every model at every provider
Where it sits
Every measured value, grouped by study. Each row puts the value on its own track, with the other configurations of the same chart as muted dots. A range is the fastest to slowest recorded run and p50–p95 is the median to the 95th percentile; neither is a confidence interval. Use Table for the plain values.
| Metric | Value | n | Interval or range | Configuration |
|---|---|---|---|---|
| Pass rate on five validated tasks | 100% (15/15) | 15 | 80%–100% (95% CI) | Claude Code · five short validated tasks |
| Total time per call | 1.94 s | 15 | 1.4 s–9.8 s (range) | Claude Code · five short validated tasks |
| Time to first useful output | 1.20 s | 15 | 1 s–7.9 s (range) | Claude Code · five short validated tasks |
| Input tokens per call: what the CLI sends (Cache read) | 2,760 | 15 | — | Claude Code · five short validated tasks |
| Input tokens per call: what the CLI sends (Other input) | 473 | 15 | — | Claude Code · five short validated tasks |
| Output tokens per call (Output tokens) | 64 | 15 | — | Claude Code · five short validated tasks |
| List-price cost per call (calculation) Calculation | $0.0099 | 15 | $0.0049–$0.058 (range) | Claude Code · five short validated tasks |
| List-price cost per passing answer (calculation) Calculation | $0.021 | 15 | — | Claude Code · five short validated tasks |
Whiskers: 95% Wilson intervalLines: fastest–slowest run (not an interval)n beside each valueMuted dots: the other configurations on the same chartHollow: list-price calculation
Claude Fable 5.1 in Haiku vs Sonnet vs Opus vs Fable vs Codex: a timed head-to-head: 8 values, first Pass rate on five validated tasks 100% (15/15).
| Metric | Value | n | Interval or range | Configuration |
|---|---|---|---|---|
| Pass rate on eight hard tasks (Strict pass) | 100% (24/24) | 24 | 86%–100% (95% CI) | Claude Code · eight hard validated tasks |
| Pass rate on eight hard tasks (Lenient (format misses counted)) | 100% (24/24) | 24 | 86%–100% (95% CI) | Claude Code · eight hard validated tasks |
| Total time per call on hard tasks (separate batches) | 16.1 s | 24 | 4.5 s–90 s (range) | Claude Code · eight hard validated tasks |
| Time to first useful output on hard tasks | 11.6 s | 24 | 2 s–85.3 s (range) | Claude Code · eight hard validated tasks |
| Output tokens per call on hard tasks (Output tokens) | 1,366 | 24 | — | Claude Code · eight hard validated tasks |
| List-price cost per strict pass on hard tasks (calculation) Calculation | $0.093 | 24 | — | Claude Code · eight hard validated tasks |
Whiskers: 95% Wilson intervalLines: fastest–slowest run (not an interval)n beside each valueMuted dots: the other configurations on the same chartHollow: list-price calculation
Claude Fable 5.1 in Haiku vs Sonnet vs Opus vs Fable vs GPT-6.1 Sol on 8 hard tasks: 6 values, first Pass rate on eight hard tasks (Strict pass) 100% (24/24).
| Metric | Value | n | Interval or range | Configuration |
|---|---|---|---|---|
| Thought experiment: the same tokens at other list prices Calculation | $12.85 | — | — | calculation: Agent’s recorded tokens at this model’s list price |
| Thought experiment: what prompt caching saved (With caching (as recorded)) Calculation | $321.31 | — | — | calculation: Agent’s recorded tokens at this model’s list price |
| Thought experiment: what prompt caching saved (Without caching) Calculation | $1716.65 | — | — | calculation: Agent’s recorded tokens at this model’s list price |
n beside each valueMuted dots: the other configurations on the same chartHollow: list-price calculation
Claude Fable 5.1 in What if every call ran on Opus? Repricing real agent tokens: 3 values, first Thought experiment: the same tokens at other list prices $12.85.
Prompt cache break-even: after how many reuses does a cached prefix cost less?
3 values · open the study
| Metric | Value | n | Interval or range | Configuration |
|---|---|---|---|---|
| Reuses before a cached prefix costs less, by model and write type (calculation) (1-hour write (2× input), whole prefix new) Calculation | 1.03 | — | — | calculation: Agent’s recorded tokens at this model’s list price |
| Reuses before a cached prefix costs less, by model and write type (calculation) (1-hour write, pooled n = 6 session share, 19% already cached (as recorded)) Calculation | 0.65 | — | — | calculation: Agent’s recorded tokens at this model’s list price |
| Reuses before a cached prefix costs less, by model and write type (calculation) (5-minute write (1.25× input, an assumption)) Calculation | 0.26 | — | — | calculation: Agent’s recorded tokens at this model’s list price |
n beside each valueMuted dots: the other configurations on the same chartHollow: list-price calculation
Claude Fable 5.1 in Prompt cache break-even: after how many reuses does a cached prefix cost less?: 3 values, first Reuses before a cached prefix costs less, by model and write type (calculation) (1-hour write (2× input), whole prefix new) 1.03.
| Metric | Value | n | Interval or range | Configuration |
|---|---|---|---|---|
| Reasoning share of output tokens per call on hard tasks (calculation) Calculation | 64.2% | 24 | 23%–97% (range) | Claude Code |
| List-price cost per call: reasoning, remaining output and input (calculation) (Reasoning (output tokens)) Calculation | $0.054 | 24 | — | Claude Code |
| List-price cost per call: reasoning, remaining output and input (calculation) (Remaining output (visible-answer estimate)) Calculation | $0.019 | 24 | — | Claude Code |
| List-price cost per call: reasoning, remaining output and input (calculation) (Input (prompt, cache priced)) Calculation | $0.021 | 24 | — | Claude Code |
| Reasoning share on short tasks vs hard tasks (calculation) (Eight hard tasks) Calculation | 64.2% | 24 | 23%–97% (range) | Claude Code |
| Reasoning share on short tasks vs hard tasks (calculation) (Five short tasks) Calculation | 0% | 15 | 0%–74% (range) | Claude Code |
Lines: lowest–highest run (not an interval)n beside each valueMuted dots: the other configurations on the same chartHollow: list-price calculation
Claude Fable 5.1 in How much of an AI bill is thinking? Reasoning tokens by model and effort: 6 values, first Reasoning share of output tokens per call on hard tasks (calculation) 64.2%.
| Metric | Value | n | Interval or range | Configuration |
|---|---|---|---|---|
| Time to first text: a 250-line answer, six models | 4.43 s | 4 | 2.3 s–4.6 s (range) | Claude Code |
| Output speed after the first text: visible tokens per second (calculation) Calculation | 123 | 4 | 121–131 (range) | Claude Code |
| Output speed in characters per second after the first text (calculation) Calculation | 273 | 4 | 270–293 (range) | Claude Code |
Lines: fastest–slowest run (not an interval)n beside each valueMuted dots: the other configurations on the same chartHollow: list-price calculation
Claude Fable 5.1 in Where the seconds go: first text, output speed and prompt size for 6 LLMs: 3 values, first Time to first text: a 250-line answer, six models 4.43 s.
Compare Claude Fable 5.1
Each bar counts the rows of one comparison: a side ahead only where its interval or range is apart, otherwise a tie or unclear.
vs model
Claude Opus 5.5 vs Claude Fable 5.1
5 ties · 18 unclear
vs model
Claude Sonnet 5.5 vs Claude Fable 5.1
4 ties · 19 unclear
vs model
Claude Fable 5.1 vs GPT-6.1 Sol (Codex CLI)
3 ties · 20 unclear
vs model
Claude Haiku 4.5 vs Claude Fable 5.1
Claude Fable 5.1 ahead on 2 · 1 tie · 20 unclear
Watch
Agent Benchmarks, October 2026: 28 studies in one film
The headline of each of our 28 open benchmark studies, with sample sizes and intervals. Calculations labelled; failures counted.
Transcript
- October 2026 roundup · 28 studies. Agent Benchmarks: every headline. Recorded runs, 95% intervals where they exist, every failure counted. Calculations labelled.
- SWE-bench Verified: Agent resolved 25 of 33. The public panel averaged 74.1%; the intervals overlap, so no rank. Agent resolved (one attempt each): 76% (25/33) (n = 33, 95% CI 59–87%). Public panel mean, same instances: 74.1% (n = 33). Model cost per resolved instance (calculation, notional): $3.71 (n = 25). Caveat: n = 33: intervals are wide. This is a defect-finding run, not a ranking.
- SWE-bench, interim (3 of 8 pairs graded): Opus 5.5 as Agent’s brain resolved 2 of 3, Sonnet 5.5 1 of 3. Exact McNemar p = 1.0: no difference yet. Opus cost 2.6× as much, a calculation. Opus 5.5 in Agent: resolved (interim): 67% (2/3) (n = 3, 95% CI 21–94%). Sonnet 5.5 in Agent: same instances: 33% (1/3) (n = 3, 95% CI 6–79%). List-price cost, Opus vs Sonnet (calculation): 2.6× (n = 3). Caveat: Different platform builds: Opus ran on 4f6f4027; the Sonnet attempts ran on f0ac3a8a and 236c0d3f. Platform changes can move results by themselves, so a gap compares Sonnet on an older platform with Opus on the current one, not the models alone.
- Blind critics preferred the AI pull request to the merged human one on 9 of 12 tasks at the latest attempt, 6 of 12 at the first. AI preferred, latest attempt: 75% (9/12) (n = 12, 95% CI 47–91%). AI preferred, first scored attempt: 50% (6/12) (n = 12, 95% CI 25–75%). Single critic verdicts for the AI change: 69% (91/132) (n = 132, 95% CI 61–76%). Caveat: Most critics are Anthropic models, and the worker runs on an Anthropic model. Same-family preference is possible; the per-critic chart shows the OpenAI critics’ share.
- Five short tasks, nine setups: 127 of 130 calls passed, so speed and tokens separate them. Fastest median: Fable 5.1 at 1.9 s. Calls that passed their validator: 98% (127/130) (n = 130, 95% CI 93–99%). Fastest median total time (Fable 5.1): 1.9 s (n = 15). Median input tokens per call: Codex CLI vs Claude Code: 12,124 vs 2,130 (n = 130). Caveat: CLI timings include CLI start-up and the CLI’s own system prompt.
- Eight hard tasks: Sonnet 5.5, Opus 5.5, Opus 5.5 high, GPT-6.1 Sol medium, Fable 5.1 and GPT-6.1 Sol high passed every call (24/24 or 16/16). Haiku 4.5 passed 11/24. Chart: Eight hard tasks · strict pass rate · 95% intervals (n = 16–24 each). Caveat: Claude Code and Codex CLI rows pair a CLI with a model, and each CLI adds its own system prompt and start-up time. A Claude-vs-GPT row compares the route + model pairs, not the models alone.
- Coding agents on hidden-test tasks: 36 of 36 sessions passed, so time separates them. Claude Code with Sonnet 5.5: median 23.1 s; Codex CLI took 4.9× as long, with extra standing instructions. Sessions that passed every hidden check: 100% (36/36) (n = 36, 95% CI 90–100%). Median time, Sonnet 5.5 in Claude Code: 23.1 s (n = 12). Median time, Codex CLI vs Claude Code with Sonnet: 4.9× (n = 12). Caveat: Codex CLI ran with the tester’s global AGENTS.md: --ignore-user-config does not switch that file off. 12 of 12 Codex sessions read the tester’s notes, 10 wrote a WORKLOG.md and 9 reported a commit attempt. Its time, tool calls and lines changed include that work. Claude Code ran with setting sources off, and no Claude session did any of it.
- Effort ladder: 11 model and effort settings passed 176 of 176 calls strictly (16/16 each, 81%–100%). No effort level wins any of 172 rows. Calls that passed strictly, low to high effort: 100% (176/176) (n = 176, 95% CI 98–100%). Model and effort configurations: 11 (6 new, 5 reference). Effort comparison rows where one level wins: 0 (of 172 rows · 16 pairs). Caveat: Every cell passed every call, so the set has a ceiling: a perfect 16/16 has a 95% interval of 81% to 100%. This study cannot show that effort does not matter on harder work; it shows that these 8 tasks do not need more than low effort.
- Caching, a list-price calculation: 50% less on Sonnet 5.5, 53% on Opus 5.5. Same prompt 10 times: 7 of 9 cells passed every time. Sonnet 5.5 session cost saved by the cache (calculation): 50% ($0.1350 vs $0.2698). Later sessions that reused an earlier session’s cache: 0 of 4. Model-and-prompt cells that passed 10 of 10: 7 of 9. Caveat: Cross-session reuse did not happen here. The cause was not tested: the CLI may add per-process context before the user message. Do not read it as a provider property.
- Agent memory: Sonnet 5.5 followed team-only rules 40% (6/15) of the time without memory and 100% (15/15) with an 11-line file. Without the late-fee rate it asked 7/9 times. Team knowledge, no memory: 40% (6/15) (n = 15, 95% CI 20–64%). Team knowledge, 11-line file: 100% (15/15) (n = 15, 95% CI 80–100%). Asked for the missing rate: 7/9. Caveat: One small synthetic repository and one author of the facts: the curated file is an upper bound written with knowledge of the tasks.
- System One arena: on 1,085 checkable decisions, Jev 1.13 answered 76.8% right; the best open model, Clef 27B, 69.9%. Jev 1.13: 76.8% (805/1048) (n = 1048, 95% CI 74–79%). Clef 27B: 69.9% (733/1048) (n = 1048, 95% CI 67–73%). Checkable decisions: 1,085. Caveat: Local models ran quantized on one Mac; the vendors measured full-precision weights on data-centre GPUs. Latency on other hardware will differ, and Jev latency includes the network.
- Routing: Jev 74/82, Haiku 4.5 73/82, Sonnet 5.5 77/82 exact, and the intervals overlap. List-price cost is where they differ. Chart: Cost per 1,000 routing decisions (n = 82–246 each). Calculation, not a run. Caveat: The case sets and question wording were revised in fix waves against Jev answers on 2026-10-04 and 2026-10-05, so Jev has a home advantage.
- Routing overhead: an in-process policy decides in 1.42 µs; Sonnet 5.5 as a router takes 2.60 s through the CLI, about 1.8 million times longer. Chart: Time per routing decision · log scale · median to p95 (n = 82–20000 each). Caveat: The policy is timed in process and the LLM routers through a CLI: this compares the two ways of routing as deployed, not two models on equal footing. A direct API call would skip the CLI time (shown separately).
- Provider prices, reported by OpenRouter: open-weight models vary up to 12.6x across providers. Closed models: one price, plus a 5.5% credit fee. Largest price spread (DeepSeek V4 Flash 0423): 12.6x (15 providers · blended price). Gateway price equals the first-party price: 10 of 10. Endpoints in the snapshot: 265 endpoints (52 providers, 27 models). Caveat: Every price is third-party-reported by OpenRouter’s API at 2026-10-06. Prices change often; refetch before relying on them.
- Recorded SWE-bench tokens, repriced: $87.23 on Sonnet 5.5, $143.83 on Opus 5.5, $343.33 with no prompt cache. At Sonnet 5.5 prices (the model that ran): $87.23 (n = 33). At Opus 5.5 prices: $143.83 (n = 33). Sonnet 5.5 without the prompt cache: $343.33 (n = 33). Calculation, not a run. Caveat: Every repriced figure is a calculation, not a run. Only the Sonnet 5.5 row matches the model that produced the tokens.
- What a CLI adds: for a one-line answer the Codex CLI was 3.5x slower than the API and sent 19,551 input tokens. Codex CLI vs OpenAI API, one-line answer: 3.5x slower (n = 30). Input tokens the Codex CLI sends for one line: 19,551 (n = 15). Scheduler repair, median: Claude Code vs Codex CLI: 15.0 s vs 61.2 s (n = 3, models differ too). Caveat: Small samples: 3 to 5 runs per configuration. Medians with ranges, not intervals.
- Three real pull requests: the latest build verified 1 of 3, at $11.06 notional. Guardrail refusals went 26 → 19. Verified deliveries, latest build: 1 of 3 (n = 3). Notional cost, latest build, 3 tasks: $11.06 (n = 3). Guardrail refusals, first vs latest slice: 26 → 19 (n = 3). Caveat: One attempt per cell: these are defect-finding runs, not rates.
- Agent-loop strict passes: Haiku 54% (13/24); Sonnet 100% (16/16). Attempts excluded for outside reads: 2 of 56. Claude Haiku 4.5 strict pass rate, agent loop: 54% (13/24) (n = 24, 95% CI 35–72%). Claude Sonnet 5.5 strict pass rate, agent loop: 100% (16/16) (n = 16, 95% CI 81–100%). Agent-loop attempts left out for reading outside the work folder: 2 of 56 (n = 56). Caveat: The Claude single-call cells ran in another batch on 2026-10-06 (03:23 to 04:02 UTC), with the same CLI version, tasks and validators; provider load can differ by hour.
- Haiku exact routing: thinking off 87% (71/82), on 89% (73/82). Paired McNemar p = 0.754; day and account differ. Claude Haiku 4.5 (thinking off): exact routing decisions: 87% (71/82) (n = 82, 95% CI 78–92%). Claude Haiku 4.5 (thinking on): exact routing decisions: 89% (73/82) (n = 82, 95% CI 80–94%). Paired exact test, thinking off vs on (exact McNemar p): 0.754 (n = 82). Caveat: The thinking-on and Sonnet arms are the recorded routing run of 2026-10-05, reused. The thinking-off arm ran on a different day and on a different Claude subscription account, so this is a confounded comparison. Day, account, CLI version and input-token differences can affect the results. The data cannot isolate the effect of thinking.
- Format misses: instructions 35% (17/48), JSON schema 0% (0/48). The schema still gave wrong values: 13% (6/48). Format-miss rate with instructions only, all models: 35% (17/48) (n = 48, 95% CI 23–50%). Format-miss rate with a JSON schema, all models: 0% (0/48) (n = 48, 95% CI 0–7%). Wrong-values rate with a JSON schema, all models: 13% (6/48) (n = 48, 95% CI 6–25%). Caveat: Small samples: Haiku 24 calls per mode, Sonnet 12 calls per mode and GPT-6.1 Sol 12 calls per mode. A 12/12 result has a 95% interval of 76% to 100%. This is not a minimum detectable difference.
- Later Claude sessions with substantial cache reuse: new folders 0 of 2 (95% interval 0% to 66%); a fixed folder 2 of 2 (95% interval 34% to 100%). This analysis is exploratory. Later sessions with at least 50% of turn-1 input cached, A: new folder each time: 0 of 2 (95% interval 0% to 66%) (n = 2, 95% CI 0–66%). Later sessions with at least 50% of turn-1 input cached, B: fixed folder: 2 of 2 (95% interval 34% to 100%) (n = 2, 95% CI 34–100%). Caveat: The surviving protocol file was created after all counted calls. Its claimed 00:32 UTC declaration is not supported by its file birth time. Amendment 1 and 2 state 00:36 and 00:37 UTC, but separate pre-edit copies do not verify those times. The current summary was regenerated at 07:41 UTC. Treat the analysis as exploratory.
- Cache break-even, a calculation: a new prefix with a one-hour write needs 2 reuses (the 3rd request). Recorded session payback: 2 turns (6 of 6 sessions). Reuses before a 1-hour cached prefix costs less, whole prefix new (calculation): 2 reuses (the 3rd request). Turn at which a recorded Claude Code session’s total input cost with the cache first fell below its cost with no cache (calculation on recorded tokens): 2 turns (6 of 6 sessions) (n = 6). Calculation, not a run. Caveat: The retained Claude protocol file was created at 14:43:55 UTC, after the first counted session at 14:35:39 UTC on 2026-10-06. Its declaration says 14:25 UTC, but file times do not verify that claim. Treat this as a retrospective protocol record.
- Exact unseen routing decisions: Jev 82% (46/56), Haiku 79% (44/56), Sonnet 88% (49/56). The intervals overlap; no rank. Jev 1.13 (TypeSafe): exact on unseen decisions: 82% (46/56) (n = 56, 95% CI 70–90%). Claude Haiku 4.5 · Claude Code: exact on unseen decisions: 79% (44/56) (n = 56, 95% CI 66–87%). Claude Sonnet 5.5 (low) · Claude Code: exact on unseen decisions: 88% (49/56) (n = 56, 95% CI 76–94%). Caveat: The case author and two of the three routers are Claude models, so a same-family label bias is possible. A second labeller (GPT-6.1 Sol) labelled every case blind; the secondary scoring keeps only the keys where its label is inside our acceptable set.
- Reasoning cost at high vs low effort, a calculation from recorded calls: Sonnet 2.2x ($0.0043 at low, $0.0094 at high); Opus 3.6x ($0.0050 at low, $0.0180 at high). Reasoning cost per call, high ÷ low effort, Claude Sonnet 5.5 · Claude Code (calculation, means): 2.2x ($0.0043 at low, $0.0094 at high) (n = 16). Reasoning cost per call, high ÷ low effort, Claude Opus 5.5 · Claude Code (calculation, means): 3.6x ($0.0050 at low, $0.0180 at high) (n = 16). Calculation, not a run. Caveat: The hard-set protocol file was created after its first counted call. Both effort-ladder protocol files were created after their batches ended. The short-set file predates its first call, but its top-up amendment timing is unverified. Batch receipts preserve protocol text, but we cannot verify all rules were written before inference. Treat these as exploratory calculations, not preregistered tests.
- Speed anatomy, a calculation: same-text token count ratio 1.8x. Extra time to first text with the larger prompt: Haiku +0.9 s; Sonnet +1.6 s. The same 4,327-character reply: most tokens ÷ fewest tokens across models (calculation): 1.8x (n = 23). Haiku: extra time to first text at 64k vs 1k (calculation): +0.9 s (n = 6). Sonnet: extra time to first text at 64k vs 1k (calculation): +1.6 s (n = 6). Calculation, not a run. Caveat: 4 calls per model in part A and 3 per size in part B. Medians of so few calls move with one slow call, and the ranges are not confidence intervals. The 95% Wilson intervals on the lookup rates are wide.
- Cost per correct answer, a calculation: Sonnet every time $0.0132; Haiku with one retry then Sonnet $0.0566. No policy ran. Cost per correct answer, Sonnet 5.5 every time (calculation): $0.0132 (n = 24). Cost per correct answer, Haiku with one retry then Sonnet (calculation): $0.0566 (n = 48). Calculation, not a run. Caveat: Advance registration is not verified. The hard-set protocol file birth time is 2026-10-06 04:03:37 UTC; its first counted call started at 03:23:59 UTC. The ladder protocol file birth time is 14:35:11 UTC; its first Claude call started at 14:21:50 UTC. Both files claim advance declaration, but the available file times do not support that claim. Copying could explain the times; we cannot establish it.
- Strict passes on four selected harder tasks: Sol 69% (11/16); Opus 42% (5/12); Sonnet 38% (6/16). Tasks were selected with a Sonnet pilot. GPT-6.1 Sol (medium) (Codex CLI): strict pass rate on the harder tasks: 69% (11/16) (n = 16, 95% CI 44–86%). Opus 5.5 (Claude Code): strict pass rate on the harder tasks: 42% (5/12) (n = 12, 95% CI 19–68%). Sonnet 5.5 (Claude Code): strict pass rate on the harder tasks: 38% (6/16) (n = 16, 95% CI 18–61%). Caveat: Selection effect: the study picked tasks that Sonnet did not pass twice in the pilot. Sonnet passed 2 of 8 pilot calls on the kept tasks and 6 of 16 counted calls (calculation: 25% and 38%; the intervals overlap). Selection can produce this pattern, but the run does not establish its cause.
- Latency budget, a calculation: steps within an assumed 300 ms budget 3 of 14 (median: 3 of 14); within 1,500 ms 4 of 14 (median: 8 of 14), at p95 or the observed maximum. No voice turn ran. Steps that fit a 300 ms budget at the slow end (calculation): 3 of 14 (median: 3 of 14) (n = 14). Steps that fit a 1,500 ms budget at the slow end (calculation): 4 of 14 (median: 8 of 14) (n = 14). Calculation, not a run. Caveat: Timing samples omit 0 failed or untimed matched explorer calls and 0 failed or untimed Claude head-to-head calls. A failure is not a fast successful step. No pass rate is estimated here.
- Routing cost at an assumed million decisions a day, a calculation: Jev $33.70; Sonnet $7,324. No load test ran. Daily cost at 1 million decisions, Jev (calculation): $33.70 (n = 82). Daily cost at 1 million decisions, Sonnet 5.5 router (calculation): $7,324 (n = 82). Calculation, not a run. Caveat: The routing and live Jev protocols predate the first counted calls by file birth time. The overhead protocol predates its microbenchmark output. Claude ran 82 calls per router, below its 120-call cap. Jev ran 246 counted calls, below its 300-call cap. One Haiku pilot and one Jev probe are excluded. All counted calls completed without call errors. The policy microbenchmark used 5,000 warm-up iterations and 64 synthetic contexts; the minimum and individual timing samples are unavailable, so we cannot rebuild its quantiles or full range. No separate validator-control receipt or Sonnet pilot is retained.
- 28 studies, one place. Intervals, sources and every failure kept.
Haiku vs Sonnet vs Opus vs Fable vs GPT-6.1 Sol on eight hard tasks
139 of 152 calls passed strictly. 6 configurations passed every call; Haiku 4.5 passed 11/24. Medians with ranges; costs are calculations.
Transcript
- Hard head-to-head · 152 scored calls · 7 configurations. Haiku vs Sonnet vs Opus vs Fable vs GPT-6.1 Sol. Strict validators, tested against controls first. Every call kept, nothing retried.
- 139 of 152 calls passed strictly. 6 configurations passed every call; Haiku 4.5 passed 11/24. Calls that passed strictly: 91% (139/152) (n = 152, 95% CI 86–95%). Configurations that passed every call: 6 of 7 (4 at 24/24, 2 at 16/16) (n = 7). Codex CLI attempts blocked before any model call (not scored): 30 (of 182 attempts). Caveat: Claude Code and Codex CLI rows pair a CLI with a model, and each CLI adds its own system prompt and start-up time. A Claude-vs-GPT row compares the route + model pairs, not the models alone.
- Perfect: 4 at 24/24 (86%–100%), 2 at 16/16 (81%–100%), 95% intervals. Haiku 4.5 at 11/24 (28%–65%). Chart: Strict pass rate · 95% Wilson intervals (n = 16–24 each). Caveat: 6 configurations passed every call, so the hard set still has a ceiling for them: a perfect 24/24 has a 95% interval of 86% to 100%; a perfect 16/16 has a 95% interval of 81% to 100%. Among them, only the latency, token and cost medians differ, and their per-call time ranges overlap.
- Haiku 4.5 passed none of event-loop order, room schedule and SQL report query. 5 more replies were right but in the wrong format. Table: Every call, task by task · 3 or 2 calls per cell. Caveat: Claude Code: n = 24 per configuration (3 repetitions per task); Codex CLI: n = 16 per configuration (2 repetitions per task). Per-task cells have only 2 to 3 calls.
- Median time per call: Sonnet 5.5 7.7 s, GPT-6.1 Sol 13.1 s and 18.1 s, Haiku 4.5 39.0 s. The ranges overlap: no speed ranking. Chart: Median total time per call · whiskers: fastest to slowest call (n = 16–24 each). Caveat: Strict format rules decide part of the result: a reply in a code fence fails. The lenient reading is shown next to it so the two can be told apart.
- Quality vs list-price cost per strict pass, a calculation: Sonnet 5.5 at $0.0143 is the frontier alone. Chart: Quality vs cost frontier on hard tasks (n = 16–24 each). Calculation, not a run. Caveat: Default effort means the effort flag was not passed; the CLI chose. Haiku reported a median 4,556 reasoning tokens per call, which explains much of its extra time and output.
- Open benchmarks: intervals, sources and every failure kept.
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