Knowledge
Like-for-like- Claude Sonnet 4.6
- 66.0
- Qwen3.7 Max
- 64.2
- Weighted basis
- 4 vs 4 rows
- Reading
- Claude Sonnet 4.6 leads
Five or fewer confirmed AI changes, with original sources, on mornings when something changed.A free source-linked morning brief.
Start free briefUpdated August 18, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
Qwen3.7 Max has the higher public score estimate, 71.6 versus 64.53, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
8 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.
Prompts that approach the documented context limit
Qwen3.7 Max
Qwen3.7 Max has the larger documented context window.
Confidence: documented
Code generation, repair, and software-engineering tasks
Not enough matched evidence
The category averages use different weighted benchmark sets, so they are directional rather than like-for-like.
Confidence: limited
Tool use, computer use, and multi-step task completion
Not enough matched evidence
The category averages use different weighted benchmark sets, so they are directional rather than like-for-like.
Confidence: limited
1K fresh input + 500 output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. Claude Sonnet 4.6 does not fit this workload in one request. Claude Sonnet 4.6 has no published cached-input rate, so cached tokens use its listed input rate. Qwen3.7 Max has no comparable published API token rate.
Confidence: rate-fallback
50K fresh input + 3K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
2 categories use different evidence sets. Those rows remain visible for coverage context but do not name a winner.
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 Sonnet 4.6 | Qwen3.7 Max | Weighted basis | Reading |
|---|---|---|---|---|
| Knowledge | 66.0 | 64.2 | Like-for-like4 vs 4 rows | Claude Sonnet 4.6 leads |
| Agentic | 65.2 | 69.7 | Directional only2 vs 1 rows | Directional only |
| Coding | 69.1 | 77.9 | Directional only2 vs 4 rows | Directional only |
| Reasoning | Not measured | 90.4 | Not comparable0 vs 1 rows | Not comparable |
| Math | 26.4 | 97.1 | Not comparable2 vs 1 rows | Not comparable |
| Multilingual | Not measured | 87.0 | Not comparable0 vs 1 rows | Not comparable |
| Multimodal | 77.4 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Instruction following | Not measured | 84.4 | Not comparable0 vs 2 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.
SuperGPQA
Knowledge
Terminal-Bench 2.0
Agentic
MMLU-Pro
Knowledge
HLE
Knowledge
GPQA
Knowledge
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
Qwen3.7 Max has no comparable published API token rate.
50K fresh input + 3K output tokens
Qwen3.7 Max has no comparable published API token rate.
200K cached + 20K fresh input + 10K output tokens
Claude Sonnet 4.6 does not fit this workload in one request. Claude Sonnet 4.6 has no published cached-input rate, so cached tokens use its listed input rate. Qwen3.7 Max has no comparable published API token rate.
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 Sonnet 4.6
200K
Qwen3.7 Max
1M
Claude Sonnet 4.6
Not sourced
Qwen3.7 Max
Not sourced
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Claude Sonnet 4.6
Not published
Qwen3.7 Max
No comparable hosted API rate
Claude Sonnet 4.6
Not sourced
Qwen3.7 Max
Not sourced
Claude Sonnet 4.6
Not sourced
Qwen3.7 Max
Not sourced
Claude Sonnet 4.6
Not sourced
Qwen3.7 Max
Not sourced
Claude Sonnet 4.6
Non-Reasoning
Qwen3.7 Max
Reasoning
Claude Sonnet 4.6
Proprietary
Qwen3.7 Max
Proprietary
Claude Sonnet 4.6
Proprietary
Qwen3.7 Max
Proprietary
Claude Sonnet 4.6
2026-02-01
Qwen3.7 Max
2026-05-16
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 2.0
Qwen3.7 Max leads this result
OSWorld-Verified
Not directly comparable
Claw-Eval
Claude Sonnet 4.6 leads this result
CyberGym
Not directly comparable
Gert Labs
Shared sourceQwen3.7 Max leads this result
OSWorld 2.0
Not directly comparable
JobBench
Not directly comparable
QwenClawBench
Not directly comparable
BFCL v4
Not directly comparable
MCP Atlas
Not directly comparable
VITA-Bench
Not directly comparable
HLE w/ tools
Not directly comparable
ResearchClawBench
Not directly comparable
SWE-bench Verified
Qwen3.7 Max leads this result
SWE-Rebench
Not directly comparable
React Native Evals
Not directly comparable
Vibe Code Bench
Not directly comparable
cursorBench31
Not directly comparable
FrontierCode 1.1 Main
Not directly comparable
EEBench
Not directly comparable
CADGenBench Generation
Not directly comparable
SWE-bench Pro
Not directly comparable
SWE Multilingual
Not directly comparable
NL2Repo
Not directly comparable
SciCode
Not directly comparable
LiveCodeBench
Not directly comparable
Terminal-Bench 2.0
Not directly comparable
GPQA
Qwen3.7 Max leads this result
SuperGPQA
Claude Sonnet 4.6 leads this result
MMLU-Pro
Qwen3.7 Max leads this result
HLE
Claude Sonnet 4.6 leads this result
GPQA-D
Not directly comparable
MMLU-Redux
Not directly comparable
MMMLU
Not directly comparable
FrontierMath v2 (Tiers 1-3)
Not directly comparable
FrontierMath v2 (Tier 4)
Not directly comparable
HMMT Feb 2026
Not directly comparable
IMOAnswerBench
Not directly comparable
Apex
Not directly comparable
MMLU-ProX
Not directly comparable
NOVA-63
Not directly comparable
INCLUDE
Not directly comparable
MAXIFE
Not directly comparable
PolyMath
Not directly comparable
CharXiv
Not directly comparable
Qwen3.7 Max has the higher public score estimate, 71.6 versus 64.53, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.
The current coding averages use different weighted benchmark sets, so BenchLM does not name a winner from them. Read the shared benchmark rows directly and test the models on the same task set.
The current agentic tasks averages use different weighted benchmark sets, so BenchLM does not name a winner from them. Read the shared benchmark rows directly and test the models on the same task set.
Both models do not have comparable published API token rates, so this page does not name a universal price winner.
Qwen3.7 Max has the larger documented context window: 1M, compared with 200K.
Last updated August 18, 2026
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