Anthropic
Claude Fable 5
- Benchmark records
- 11
- Snapshot
- 2026-07-30
- Release date
- 2026-06-09
Independent model comparison
Claude Fable 5 vs Claude Opus 4.6: evidence side by side
Compare the models using only evidence that can be identified and attributed. Exact benchmark matches appear first; independent facts and user reports remain separate and do not create an overall ranking.
Exact comparison coverage
3 benchmark records share an exact reviewed comparison key.
Evidence strength
Limited exact coverage
The page is useful for inspection but does not yet contain enough pair-native evidence for Search publication.
Models at a glance
Key differences
Anthropic
Claude Opus 4.6
- Benchmark records
- 3
- Snapshot
- 2026-07-17
- Release date
- 2026-02-05
| Detail | Claude Fable 5 | Claude Opus 4.6 |
|---|---|---|
| Provider |
Anthropic |
Anthropic |
| Release date Shown only where an exact reviewed release date is available. |
2026-06-09 |
2026-02-05 |
| Input price Artificial Analysis operational reference; see the attributed details below. |
$10.00 / 1M tokens |
$5.00 / 1M tokens |
| Output price Artificial Analysis operational reference; see the attributed details below. |
$50.00 / 1M tokens |
$25.00 / 1M tokens |
| Median output speed Artificial Analysis operational reference; see the attributed details below. |
65.0 tok/s |
39.0 tok/s |
| Exact benchmark coverage Only records carrying the same reviewed comparison identity are counted. |
3 shared records |
3 shared records |
Price and speed appear only when an exact reviewed operational reference is attached to that model identity.
Primary comparison evidence
Exact matched benchmark evidence
A shared benchmark name is not enough. A result appears side by side only when both model records carry the same reviewed comparison key. Duplicate or unversioned records are omitted rather than guessed into alignment.
Repository Issue Resolution
Direct OpenHands SWE-Bench outcomes for resolving real repository issues with a pinned OpenHands agent and language-model configuration.
Claude Fable 5
95.8%
OpenHands SWE-Bench resolved
Scores are official OpenHands SWE-Bench resolved percentages for exact OpenHands and model configurations, not bare-model scores or SpringPrompt predictions. Twenty-nine exact task sidecars support marginal 95% bootstrap score intervals; five rows explicitly have no interval. No full-cohort rank confidence is claimed.
Configuration: OpenHands v1.28.0 + claude-fable-5
OpenHands Index · as of 30 Jun 2026 · OpenHands · SWE-Bench 2026.06.30-3015ac6
Claude Opus 4.6
76.8%
OpenHands SWE-Bench resolved
Scores are official OpenHands SWE-Bench resolved percentages for exact OpenHands and model configurations, not bare-model scores or SpringPrompt predictions. Twenty-nine exact task sidecars support marginal 95% bootstrap score intervals; five rows explicitly have no interval. No full-cohort rank confidence is claimed.
Configuration: OpenHands v1.15.0 + claude-opus-4-6
OpenHands Index · as of 30 Jun 2026 · OpenHands · SWE-Bench 2026.06.30-3015ac6
ROASBench
A 12-month performance-marketing simulation scored on business outcomes, planning, behavior, and persona fit.
Claude Fable 5
3 configurations
Average ROASBench score
Configuration: 3 configurations compared separately
Spring Prompt · Reviewed public-catalogue SQLite projection · 12-month simulation
Claude Opus 4.6
2 configurations
Average ROASBench score
Configuration: 2 configurations compared separately
Spring Prompt · Reviewed public-catalogue SQLite projection · 12-month simulation
Structured Output Reliability
Directly measured ability to return accurate values in the requested structured schema across the benchmark's evaluated text, image and audio modalities.
Claude Fable 5
85.09%
Direct benchmark score
Point order reproduces the source's direct Overall score. Rank ranges come from overlap of marginal record-cluster bootstrap intervals for Overall; they are not simultaneous confidence intervals for rank.
Configuration: claude-fable-5
Structured Output Benchmark (SOB) · as of 17 Jul 2026 · Sob-v1@da785a8521c8954283b2989d01e54d80c4e023c6:upstream-provider-configs:temperature-0-where-supported:max-output-2048:reasoning-disabled-or-minimum-where-required:official-modality-weights
Claude Opus 4.6
85.31%
Direct benchmark score
Point order reproduces the source's direct Overall score. Rank ranges come from overlap of marginal record-cluster bootstrap intervals for Overall; they are not simultaneous confidence intervals for rank.
Configuration: Claude-Opus-4.6
Structured Output Benchmark (SOB) · as of 17 Jul 2026 · Sob-v1@da785a8521c8954283b2989d01e54d80c4e023c6:upstream-provider-configs:temperature-0-where-supported:max-output-2048:reasoning-disabled-or-minimum-where-required:official-modality-weights
Secondary context · not head-to-head
Independent signals for each model
The sources below evaluated or discussed each model independently. Putting them in adjacent columns makes them easier to inspect, but it does not make their metrics, samples, or observations directly comparable.
Attributed third-party facts
Artificial Analysis details
These facts retain their source, date, protocol, and model identity. They are contextual model-level signals—not a Spring Prompt overall score.
Claude Fable 5
Input price
$10.00 / 1M tokens
Representative configuration on the cited source page.
Artificial Analysis · as of 16 Jul 2026
Output price
$50.00 / 1M tokens
Representative configuration on the cited source page.
Artificial Analysis · as of 16 Jul 2026
Median output speed
65.0 tok/s
Median output tokens received per second after generation begins; this excludes time to first token and is not end-to-end response latency.
Artificial Analysis · as of 16 Jul 2026
Claude Opus 4.6
Input price
$5.00 / 1M tokens
Representative configuration on the cited source page.
Artificial Analysis · as of 16 Jul 2026
Output price
$25.00 / 1M tokens
Representative configuration on the cited source page.
Artificial Analysis · as of 16 Jul 2026
Median output speed
39.0 tok/s
Median output tokens received per second after generation begins; this excludes time to first token and is not end-to-end response latency.
Artificial Analysis · as of 16 Jul 2026
Anecdotal model-level reports
Initial community opinions from Reddit
Recurring themes from each model's declared observation window. They are not a representative survey and are not direct comparisons between these models.
Claude Fable 5
Initial community opinions
In the search-indexed launch-window sample, Claude Fable 5 appeared especially capable on difficult code review, architecture, and long-running agent work when tasks were tightly scoped. Reports also repeatedly noted slow interactive responses, high usage cost, and safeguards or product routing that could interrupt the expected model experience, so early results varied substantially by workflow.
Source venue: Reddit · window: 2026-06-09 to 2026-06-23 · observed items: 4
Claude Opus 4.6
Initial community opinions
In the search-indexed launch-window sample, Claude Opus 4.6 was often praised for coding, planning, context recall, and reasoning across large documents. Other users reported slow deliberation, heavy usage, terse or uneven prose, and occasional changes beyond instructions. The early picture was powerful but workflow-dependent, with closer supervision and explicit plans improving results.
Source venue: Reddit · window: 2026-02-05 to 2026-02-19 · observed items: 4
Independent early-test reports
Early technical field tests from X
Editor-paraphrased reports from independent authors in each model's fixed 14-day launch window. These selectively surfaced anecdotes are not direct head-to-head tests unless they also appear in the dedicated direct-report section above.
Claude Fable 5
Early technical field tests
Initial field demonstrations showed Fable 5 turning personal sports footage into a tailored visual-analysis overlay and building a navigable, real-scale Yosemite scene from geospatial data. Both artifacts point to strong prompt-to-product work across visual reasoning and procedural 3D, but they are self-selected demonstrations and do not establish routine reliability or failure rates.
Source venue: X · window: 2026-06-09 to 2026-06-23 · 2 tests · 2 independent authors · 2 with a method or artifact · identity reviewed
Claude Opus 4.6
Early technical field tests
Early Opus 4.6 results showed strong task accuracy in both a coding-agent evaluation and a legal-work benchmark. The coding evidence also exposed a meaningful tradeoff: slower execution and more timeouts reduced aggregate throughput despite high accuracy. The launch-window picture is therefore strong quality with workflow-dependent latency and reliability costs.
Source venue: X · window: 2026-02-05 to 2026-02-19 · 2 tests · 2 independent authors · 2 with a method or artifact · identity reviewed
X field tests remain separate from Reddit community opinions, Artificial Analysis facts, and every scored benchmark.
How to read this comparison
Spring Prompt does not name an overall winner from unrelated benchmark scores, third-party metrics, Reddit opinions, or X field-test reports.
Different benchmarks measure different constructs and may use different populations, prompts, harnesses, model revisions, tools, and score scales. This page does not average those values or infer a winner from source coverage. Test both models on your own production work before making a consequential choice.