Math
Like-for-like- Claude Opus 4.6
- 36.3
- Gemini 3.1 Pro
- 31.8
- Weighted basis
- 2 vs 2 rows
- Reading
- Claude Opus 4.6 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
Claude Opus 4.6 has the higher public score estimate, 67.98 versus 56.49, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
17 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.
1K fresh input + 500 output tokens
Gemini 3.1 Pro
Gemini 3.1 Pro 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
Gemini 3.1 Pro
Gemini 3.1 Pro has the lower estimated token cost for this stated workload. Claude Opus 4.6 has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback
50K fresh input + 3K output tokens
Gemini 3.1 Pro
Gemini 3.1 Pro 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
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
Confidence: documented
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
1 category uses 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 4.6 | Gemini 3.1 Pro | Weighted basis | Reading |
|---|---|---|---|---|
| Math | 36.3 | 31.8 | Like-for-like2 vs 2 rows | Claude Opus 4.6 leads |
| Multimodal | 77.3 | 82.6 | Directional only1 vs 2 rows | Directional only |
| Agentic | 73.0 | Not measured | Not comparable3 vs 0 rows | Not comparable |
| Coding | 68.1 | Not measured | Not comparable3 vs 0 rows | Not comparable |
| Reasoning | Not measured | 77.1 | Not comparable0 vs 1 rows | Not comparable |
| Knowledge | 69.1 | Not measured | Not comparable4 vs 0 rows | Not comparable |
| Multilingual | Not measured | Not measured | Not comparable0 vs 0 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.
MMMU-Pro
Multimodal
FrontierMath v2 (Tier 4)
Math
FrontierMath v2 (Tiers 1-3)
Math
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
Gemini 3.1 Pro has the lower modeled cost
Costs use the listed standard API rates.
50K fresh input + 3K output tokens
Gemini 3.1 Pro has the lower modeled cost
Costs use the listed standard API rates.
200K cached + 20K fresh input + 10K output tokens
Gemini 3.1 Pro has the lower modeled cost
Claude Opus 4.6 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.
Claude Opus 4.6
1M
Gemini 3.1 Pro
Claude Opus 4.6
Not sourced
Gemini 3.1 Pro
gemini-3.1-pro-preview
Google Gemini 3.1 Pro Preview model documentationA missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Claude Opus 4.6
Not published
Gemini 3.1 Pro
$0.2 per 1M cached input tokens
Google Gemini API pricingClaude Opus 4.6
Not sourced
Gemini 3.1 Pro
text, image, video, audio, pdf
Google Gemini 3.1 Pro Preview model documentationClaude Opus 4.6
Not sourced
Gemini 3.1 Pro
Claude Opus 4.6
Not sourced
Gemini 3.1 Pro
Preview · Gemini API, Google AI Studio
Google Gemini model catalogClaude Opus 4.6
Non-Reasoning
Gemini 3.1 Pro
Reasoning
Claude Opus 4.6
Proprietary
Gemini 3.1 Pro
Proprietary
Claude Opus 4.6
Proprietary
Gemini 3.1 Pro
Proprietary
Claude Opus 4.6
2026-02-01
Gemini 3.1 Pro
2026-02-19
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
Not directly comparable
BrowseComp
Not directly comparable
OSWorld-Verified
Not directly comparable
Claw-Eval
Shared sourceClaude Opus 4.6 leads this result
DeepSearchQA
Shared sourceClaude Opus 4.6 leads this result
CyberGym
Not directly comparable
Gert Labs
Shared sourceClaude Opus 4.6 leads this result
ResearchClawBench
Shared sourceClaude Opus 4.6 leads this result
JobBench
Not directly comparable
τ²-bench results
Not directly comparable
SWE-bench Verified
Not directly comparable
SWE-bench Verified*
Not directly comparable
LiveCodeBench Pro
Shared sourceGemini 3.1 Pro leads this result
SWE-bench Pro
Not directly comparable
SWE-Rebench
Not directly comparable
React Native Evals
Shared sourceClaude Opus 4.6 leads this result
Vibe Code Bench
Shared sourceClaude Opus 4.6 leads this result
FrontierCode 1.1 Main
Not directly comparable
GPQA
Not directly comparable
GPQA-D
Gemini 3.1 Pro leads this result
SuperGPQA
Not directly comparable
MMLU-Pro
Not directly comparable
MMLU-Pro (Arcee)
Not directly comparable
HLE
Not directly comparable
HLE w/o tools
Shared sourceGemini 3.1 Pro leads this result
HealthBench Hard
Shared sourceGemini 3.1 Pro leads this result
MedXpertQA (Text)
Shared sourceGemini 3.1 Pro leads this result
AIME25 (Arcee)
Not directly comparable
FrontierMath v2 (Tiers 1-3)
Shared sourceClaude Opus 4.6 leads this result
FrontierMath v2 (Tier 4)
Shared sourceClaude Opus 4.6 leads this result
MMMU-Pro
Gemini 3.1 Pro leads this result
ERQA
Shared sourceGemini 3.1 Pro leads this result
ScreenSpot Pro
Shared sourceGemini 3.1 Pro leads this result
MedXpertQA (MM)
Shared sourceGemini 3.1 Pro leads this result
CharXiv
Not directly comparable
SimpleVQA
Not directly comparable
ZeroBench
Not directly comparable
Claude Opus 4.6 has the higher public score estimate, 67.98 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 $0.0175 on Claude Opus 4.6 and $0.008 on Gemini 3.1 Pro; repository review costs $0.325 and $0.136; the cache-heavy agent loop costs $1.35 and $0.2. Claude Opus 4.6 has no published cached-input rate, so cached tokens use its listed input rate.
Both models list the same context window, 1M.
Last updated September 3, 2026
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