Knowledge
Like-for-like- Claude Opus 4.5
- 58.1
- Qwen3.6-35B-A3B
- 51.4
- Weighted basis
- 4 vs 4 rows
- Reading
- Claude Opus 4.5 leads
Five or fewer confirmed AI changes, with original sources, on mornings when something changed.A free source-linked morning brief.
Start the free Radar BriefUpdated August 29, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
Claude Opus 4.5 has the higher public score estimate, 63.91 versus 51.55, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
27 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
Qwen3.6-35B-A3B
Qwen3.6-35B-A3B 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 Opus 4.5 does not fit this workload in one request. Claude Opus 4.5 has no published cached-input rate, so cached tokens use its listed input rate. Qwen3.6-35B-A3B 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.
3 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 Opus 4.5 | Qwen3.6-35B-A3B | Weighted basis | Reading |
|---|---|---|---|---|
| Knowledge | 58.1 | 51.4 | Like-for-like4 vs 4 rows | Claude Opus 4.5 leads |
| Multimodal | 69.9 | 76.3 | Like-for-like2 vs 2 rows | Qwen3.6-35B-A3B leads |
| Agentic | 62.6 | 51.5 | Directional only2 vs 1 rows | Directional only |
| Coding | 71.7 | 73.8 | Directional only2 vs 3 rows | Directional only |
| Math | 57.5 | 88.2 | Directional only4 vs 2 rows | Directional only |
| Reasoning | 64.4 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Multilingual | 85.7 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Instruction following | 69.5 | Not measured | Not comparable2 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.
CharXiv
Multimodal
HLE
Knowledge
Terminal-Bench 2.0
Agentic
SWE-bench Pro
Coding
SWE-bench Verified
Coding
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
Qwen3.6-35B-A3B has no comparable published API token rate.
50K fresh input + 3K output tokens
Qwen3.6-35B-A3B has no comparable published API token rate.
200K cached + 20K fresh input + 10K output tokens
Claude Opus 4.5 does not fit this workload in one request. Claude Opus 4.5 has no published cached-input rate, so cached tokens use its listed input rate. Qwen3.6-35B-A3B 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 Opus 4.5
200K
Qwen3.6-35B-A3B
262K
Claude Opus 4.5
Not sourced
Qwen3.6-35B-A3B
Not sourced
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Claude Opus 4.5
Not published
Qwen3.6-35B-A3B
No comparable hosted API rate
Claude Opus 4.5
Not sourced
Qwen3.6-35B-A3B
Not sourced
Claude Opus 4.5
Not sourced
Qwen3.6-35B-A3B
Not sourced
Claude Opus 4.5
Not sourced
Qwen3.6-35B-A3B
Not sourced
Claude Opus 4.5
Non-Reasoning
Qwen3.6-35B-A3B
Reasoning
Claude Opus 4.5
Proprietary
Qwen3.6-35B-A3B
Open Weight
Claude Opus 4.5
Proprietary
Qwen3.6-35B-A3B
Open Weight
Claude Opus 4.5
2025-11-01
Qwen3.6-35B-A3B
2026-04-15
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
Claude Opus 4.5 leads this result
OSWorld-Verified
Not directly comparable
OSWorld
Not directly comparable
Claw-Eval
Qwen3.6-35B-A3B leads this result
QwenClawBench
Qwen3.6-35B-A3B leads this result
τ³-bench results
Claude Opus 4.5 leads this result
VITA-Bench
Qwen3.6-35B-A3B leads this result
DeepPlanning
Claude Opus 4.5 leads this result
Toolathlon
Claude Opus 4.5 leads this result
MCP Atlas
Qwen3.6-35B-A3B leads this result
MCP-Tasks
Not directly comparable
WideResearch
Claude Opus 4.5 leads this result
CyberGym
Not directly comparable
Gert Labs
Shared sourceClaude Opus 4.5 leads this result
JobBench
Not directly comparable
QwenWebBench
Not directly comparable
SWE-bench Verified
Claude Opus 4.5 leads this result
LiveCodeBench v6
Not directly comparable
SWE-bench Pro
Claude Opus 4.5 leads this result
SWE Multilingual
Claude Opus 4.5 leads this result
NL2Repo
Claude Opus 4.5 leads this result
Terminal-Bench 2.0
Not directly comparable
LiveCodeBench
Not directly comparable
GPQA
Claude Opus 4.5 leads this result
SuperGPQA
Claude Opus 4.5 leads this result
MMLU-Pro
Claude Opus 4.5 leads this result
MMLU-Redux
Not directly comparable
C-Eval
Claude Opus 4.5 leads this result
HLE
Claude Opus 4.5 leads this result
AIME26
Claude Opus 4.5 leads this result
HMMT Feb 2025
Claude Opus 4.5 leads this result
HMMT Nov 2025
Claude Opus 4.5 leads this result
HMMT Feb 2026
Claude Opus 4.5 leads this result
MMAnswerBench
Claude Opus 4.5 leads this result
FrontierMath v2 (Tiers 1-3)
Not directly comparable
FrontierMath v2 (Tier 4)
Not directly comparable
MMMU-Pro
Qwen3.6-35B-A3B leads this result
MathVision
Not directly comparable
CharXiv
Qwen3.6-35B-A3B leads this result
VideoMMMU
Claude Opus 4.5 leads this result
ScreenSpot Pro
Not directly comparable
V*
Not directly comparable
MMMU
Not directly comparable
RealWorldQA
Not directly comparable
OmniDocBench 1.5
Not directly comparable
SimpleVQA
Not directly comparable
CC-OCR
Not directly comparable
AI2D_TEST
Not directly comparable
RefCOCO (avg)
Not directly comparable
ODINW13
Not directly comparable
Video-MME (with subtitle)
Not directly comparable
Video-MME (w/o subtitle)
Not directly comparable
MLVU (M-Avg)
Not directly comparable
Claude Opus 4.5 has the higher public score estimate, 63.91 versus 51.55, 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.
Qwen3.6-35B-A3B has the larger documented context window: 262K, compared with 200K.
Last updated August 29, 2026
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