Coding
Like-for-like- Claude Fable 5.1
- 81.2
- GPT-5.6 Sol
- 64.6
- Weighted basis
- 1 vs 1 rows
- Reading
- Claude Fable 5.1 leads
Five or fewer confirmed AI changes, with original sources, on mornings when something changed.A free source-linked morning brief.
See the free Radar BriefUpdated September 1, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
Claude Fable 5.1 has the higher public score estimate, 82.74 versus 81.69, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
5 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.
Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.
Code generation, repair, and software-engineering tasks
Claude Fable 5.1
Claude Fable 5.1 leads on the same 1 weighted benchmark row.
Confidence: limited
Prompts that approach the documented context limit
GPT-5.6 Sol
GPT-5.6 Sol has the larger documented context window.
Confidence: documented
1K fresh input + 500 output tokens
GPT-5.6 Sol
GPT-5.6 Sol has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
200K cached + 20K fresh input + 10K output tokens
GPT-5.6 Sol
GPT-5.6 Sol has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
50K fresh input + 3K output tokens
GPT-5.6 Sol
GPT-5.6 Sol has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Tool use, computer use, and multi-step task completion
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.
| Category | Claude Fable 5.1 | GPT-5.6 Sol | Weighted basis | Reading |
|---|---|---|---|---|
| Coding | 81.2 | 64.6 | Like-for-like1 vs 1 rows | Claude Fable 5.1 leads |
| Reasoning | 90.0 | 92.5 | Like-for-like1 vs 1 rows | GPT-5.6 Sol leads |
| Agentic | Not measured | 92.0 | Not comparable0 vs 2 rows | Not comparable |
| Knowledge | 65.0 | 94.6 | Not comparable1 vs 1 rows | Not comparable |
| Math | Not measured | 87.5 | Not comparable0 vs 2 rows | Not comparable |
| Multilingual | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Multimodal | Not measured | 83.0 | Not comparable0 vs 1 rows | Not comparable |
| Instruction following | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.
Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.
SWE-bench Pro
Coding
ARC-AGI-2
Reasoning
Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.
1K fresh input + 500 output tokens
GPT-5.6 Sol has the lower modeled cost
Costs use the listed standard API rates.
50K fresh input + 3K output tokens
GPT-5.6 Sol has the lower modeled cost
Costs use the listed standard API rates.
200K cached + 20K fresh input + 10K output tokens
GPT-5.6 Sol has the lower modeled cost
Costs use the listed standard API rates.
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
Maximum documented context; output-token limits may be lower.
Claude Fable 5.1
GPT-5.6 Sol
1.05M
OpenAI model catalogClaude Fable 5.1
claude-fable-5-1
Anthropic Fable 5.1 and Mythos 5.1 launchGPT-5.6 Sol
gpt-5.6-sol
OpenAI model catalogA missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Claude Fable 5.1
$0.25 per 1M cached input tokens
Anthropic Fable 5.1 launchGPT-5.6 Sol
$0.5 per 1M cached input tokens
OpenAI pricingClaude Fable 5.1
Not sourced
GPT-5.6 Sol
text, image
OpenAI model catalogClaude Fable 5.1
Not sourced
GPT-5.6 Sol
Claude Fable 5.1
Generally Available · Claude API, Claude products, AWS, Google Cloud, Microsoft Azure
Anthropic Fable 5.1 and Mythos 5.1 launchGPT-5.6 Sol
Generally Available · OpenAI Responses API
OpenAI model catalogClaude Fable 5.1
Reasoning
GPT-5.6 Sol
Reasoning
Claude Fable 5.1
Proprietary
GPT-5.6 Sol
Proprietary
Claude Fable 5.1
Proprietary
GPT-5.6 Sol
Proprietary
Claude Fable 5.1
2026-09-01
GPT-5.6 Sol
2026-07-09
Run the same representative tasks against both endpoints before changing production traffic.
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Terminal-Bench 4.0
Not directly comparable
Terminal-Bench-Science 0.1
Not directly comparable
OSWorld 2.0
GPT-5.6 Sol leads this result
AutomationBench
Not directly comparable
Toolathlon-Verified
Not directly comparable
Toolathlon Verified Pass@3
Not directly comparable
Toolathlon Verified Pass³
Not directly comparable
Toolathlon Verified avg. turns
Not directly comparable
Terminal-Bench 3.0
Not directly comparable
Terminal-Bench 2.0
Not directly comparable
BrowseComp
Not directly comparable
CyberGym
Not directly comparable
ExploitGym
Not directly comparable
Toolathlon
Not directly comparable
SWE-bench Pro
Claude Fable 5.1 leads this result
SWE Multilingual
Not directly comparable
SWE Multimodal
Not directly comparable
deepSwe
GPT-5.6 Sol leads this result
ProgramBench
Not directly comparable
cursorBench32
Shared sourceClaude Fable 5.1 leads this result
Terminal-Bench 2.0
Not directly comparable
FrontierCode 1.1 Extended
Not directly comparable
VulcanBench v3
Not directly comparable
VulcanBench CII v1
Not directly comparable
ARC-AGI-1
Not directly comparable
ARC-AGI-2
GPT-5.6 Sol leads this result
ARC-AGI-3
Not directly comparable
GeneBench-Pro
Not directly comparable
HLE
Not directly comparable
HLE w/o tools
Not directly comparable
GPQA
Not directly comparable
GPQA-D
Not directly comparable
HealthBench Professional
Not directly comparable
HealthBench Hard
Not directly comparable
Claude Fable 5.1 has the higher public score estimate, 82.74 versus 81.69, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.
Claude Fable 5.1 leads the like-for-like coding comparison across 1 shared weighted benchmark row.
The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.
For the stated presets, chat costs $0.035 on Claude Fable 5.1 and $0.02 on GPT-5.6 Sol; repository review costs $0.65 and $0.34; the cache-heavy agent loop costs $0.75 and $0.5. Costs use the listed standard API rates.
GPT-5.6 Sol has the larger documented context window: 1.05M, compared with 1M.
Last updated September 1, 2026
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