Multimodal
Like-for-like- Gemini 3.1 Pro
- 82.6
- Qwen3.5 397B
- 79.6
- Weighted basis
- 2 vs 2 rows
- Reading
- Gemini 3.1 Pro 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 3, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
Qwen3.5 397B has the higher public score estimate, 58.11 versus 56.49, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
6 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
Gemini 3.1 Pro
Gemini 3.1 Pro has the larger documented context window.
Confidence: documented
1K fresh input + 500 output tokens
Qwen3.5 397B
Qwen3.5 397B 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
Qwen3.5 397B
Qwen3.5 397B has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Code generation, repair, and software-engineering tasks
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
Tool use, computer use, and multi-step task completion
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
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. Qwen3.5 397B does not fit this workload in one request. Qwen3.5 397B has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback
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 | Gemini 3.1 Pro | Qwen3.5 397B | Weighted basis | Reading |
|---|---|---|---|---|
| Multimodal | 82.6 | 79.6 | Like-for-like2 vs 2 rows | Gemini 3.1 Pro leads |
| Agentic | Not measured | 56.5 | Not comparable0 vs 2 rows | Not comparable |
| Coding | Not measured | 66.5 | Not comparable0 vs 2 rows | Not comparable |
| Reasoning | 77.1 | 63.2 | Not comparable1 vs 1 rows | Not comparable |
| Knowledge | Not measured | 56.6 | Not comparable0 vs 4 rows | Not comparable |
| Math | 31.8 | 90.6 | Not comparable2 vs 2 rows | Not comparable |
| Multilingual | Not measured | 84.7 | Not comparable0 vs 1 rows | Not comparable |
| Instruction following | Not measured | 92.6 | Not comparable0 vs 1 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.
MMMU-Pro
Multimodal
CharXiv
Multimodal
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
Qwen3.5 397B has the lower modeled cost
Costs use the listed standard API rates.
50K fresh input + 3K output tokens
Qwen3.5 397B has the lower modeled cost
Costs use the listed standard API rates.
200K cached + 20K fresh input + 10K output tokens
Qwen3.5 397B does not fit this workload in one request. Qwen3.5 397B has no published cached-input rate, so cached tokens use its listed input 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.
Gemini 3.1 Pro
Qwen3.5 397B
128K
Gemini 3.1 Pro
gemini-3.1-pro-preview
Google Gemini 3.1 Pro Preview model documentationQwen3.5 397B
Not sourced
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Gemini 3.1 Pro
$0.2 per 1M cached input tokens
Google Gemini API pricingQwen3.5 397B
Not published
Gemini 3.1 Pro
text, image, video, audio, pdf
Google Gemini 3.1 Pro Preview model documentationQwen3.5 397B
Not sourced
Gemini 3.1 Pro
Qwen3.5 397B
Not sourced
Gemini 3.1 Pro
Preview · Gemini API, Google AI Studio
Google Gemini model catalogQwen3.5 397B
Not sourced
Gemini 3.1 Pro
Reasoning
Qwen3.5 397B
Non-Reasoning
Gemini 3.1 Pro
Proprietary
Qwen3.5 397B
Open Weight
Gemini 3.1 Pro
Proprietary
Qwen3.5 397B
Open Weight
Gemini 3.1 Pro
2026-02-19
Qwen3.5 397B
2026-02-16
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.
Claw-Eval
Shared sourceGemini 3.1 Pro leads this result
DeepSearchQA
Not directly comparable
τ²-bench results
Not directly comparable
Gert Labs
Shared sourceGemini 3.1 Pro leads this result
ResearchClawBench
Shared sourceQwen3.5 397B leads this result
Terminal-Bench 2.0
Not directly comparable
BrowseComp
Not directly comparable
QwenClawBench
Not directly comparable
τ³-bench results
Not directly comparable
VITA-Bench
Not directly comparable
DeepPlanning
Not directly comparable
Toolathlon
Not directly comparable
MCP Atlas
Not directly comparable
MCP-Tasks
Not directly comparable
WideResearch
Not directly comparable
LiveCodeBench Pro
Not directly comparable
React Native Evals
Not directly comparable
Vibe Code Bench
Not directly comparable
SWE-bench Verified
Not directly comparable
LiveCodeBench v6
Not directly comparable
SWE-bench Pro
Not directly comparable
GPQA-D
Not directly comparable
HLE w/o tools
Not directly comparable
HealthBench Hard
Not directly comparable
MedXpertQA (Text)
Not directly comparable
GPQA
Not directly comparable
SuperGPQA
Not directly comparable
MMLU-Pro
Not directly comparable
MMLU-Redux
Not directly comparable
C-Eval
Not directly comparable
HLE
Not directly comparable
FrontierMath v2 (Tiers 1-3)
Not directly comparable
FrontierMath v2 (Tier 4)
Not directly comparable
AIME26
Not directly comparable
HMMT Feb 2025
Not directly comparable
HMMT Nov 2025
Not directly comparable
HMMT Feb 2026
Not directly comparable
MMAnswerBench
Not directly comparable
MMMU-Pro
Gemini 3.1 Pro leads this result
CharXiv
Qwen3.5 397B leads this result
ERQA
Not directly comparable
SimpleVQA
Not directly comparable
ScreenSpot Pro
Gemini 3.1 Pro leads this result
ZeroBench
Not directly comparable
MedXpertQA (MM)
Not directly comparable
MathVision
Not directly comparable
VideoMMMU
Not directly comparable
V*
Not directly comparable
IFEval
Not directly comparable
Qwen3.5 397B has the higher public score estimate, 58.11 versus 56.49, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.
The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.
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 $0.008 on Gemini 3.1 Pro and $0.0024 on Qwen3.5 397B; repository review costs $0.136 and $0.0408; the cache-heavy agent loop costs $0.2 and $0.168. Qwen3.5 397B does not fit this workload in one request. Qwen3.5 397B has no published cached-input rate, so cached tokens use its listed input rate.
Gemini 3.1 Pro has the larger documented context window: 1M, compared with 128K.
Last updated September 3, 2026
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