Math
Like-for-like- Claude Sonnet 4.6
- 26.4
- Gemini 3 Pro
- 32.9
- Weighted basis
- 2 vs 2 rows
- Reading
- Gemini 3 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
Gemini 3 Pro has the higher public score estimate, 67.41 versus 64.57, 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 Pro
Gemini 3 Pro has the larger documented context window.
Confidence: documented
1K fresh input + 500 output tokens
Gemini 3 Pro
Gemini 3 Pro 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
Gemini 3 Pro
Gemini 3 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
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. Gemini 3 Pro 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.
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 Sonnet 4.6 | Gemini 3 Pro | Weighted basis | Reading |
|---|---|---|---|---|
| Math | 26.4 | 32.9 | Like-for-like2 vs 2 rows | Gemini 3 Pro leads |
| Multimodal | 77.4 | 81.1 | Directional only1 vs 2 rows | Directional only |
| Agentic | 65.2 | Not measured | Not comparable2 vs 0 rows | Not comparable |
| Coding | 69.1 | Not measured | Not comparable2 vs 0 rows | Not comparable |
| Reasoning | Not measured | 31.1 | Not comparable0 vs 1 rows | Not comparable |
| Knowledge | 66.0 | 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.
FrontierMath v2 (Tier 4)
Math
FrontierMath v2 (Tiers 1-3)
Math
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
Gemini 3 Pro has the lower modeled cost
Costs use the listed standard API rates.
50K fresh input + 3K output tokens
Gemini 3 Pro has the lower modeled cost
Costs use the listed standard API rates.
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. Gemini 3 Pro 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 Sonnet 4.6
200K
Gemini 3 Pro
2M
Claude Sonnet 4.6
Not sourced
Gemini 3 Pro
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
Gemini 3 Pro
Not published
Claude Sonnet 4.6
Not sourced
Gemini 3 Pro
Not sourced
Claude Sonnet 4.6
Not sourced
Gemini 3 Pro
Not sourced
Claude Sonnet 4.6
Not sourced
Gemini 3 Pro
Not sourced
Claude Sonnet 4.6
Non-Reasoning
Gemini 3 Pro
Non-Reasoning
Claude Sonnet 4.6
Proprietary
Gemini 3 Pro
Proprietary
Claude Sonnet 4.6
Proprietary
Gemini 3 Pro
Proprietary
Claude Sonnet 4.6
2026-02-01
Gemini 3 Pro
2025-11-18
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
OSWorld-Verified
Not directly comparable
Claw-Eval
Not directly comparable
CyberGym
Not directly comparable
Gert Labs
Shared sourceGemini 3 Pro leads this result
OSWorld 2.0
Not directly comparable
JobBench
Shared sourceClaude Sonnet 4.6 leads this result
SWE-bench Verified
Not directly comparable
SWE-Rebench
Not directly comparable
React Native Evals
Not directly comparable
Vibe Code Bench
Shared sourceClaude Sonnet 4.6 leads this result
cursorBench31
Not directly comparable
FrontierCode 1.1 Main
Not directly comparable
ARC-AGI-2
Not directly comparable
FrontierMath v2 (Tiers 1-3)
Shared sourceGemini 3 Pro leads this result
FrontierMath v2 (Tier 4)
Shared sourceGemini 3 Pro leads this result
CharXiv
Gemini 3 Pro leads this result
MMMU-Pro
Not directly comparable
MathVision
Not directly comparable
VideoMMMU
Not directly comparable
ScreenSpot Pro
Not directly comparable
V*
Not directly comparable
Gemini 3 Pro has the higher public score estimate, 67.41 versus 64.57, 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 $0.0105 on Claude Sonnet 4.6 and $0.008 on Gemini 3 Pro; repository review costs $0.195 and $0.136; the cache-heavy agent loop costs $0.81 and $0.56. 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. Gemini 3 Pro has no published cached-input rate, so cached tokens use its listed input rate.
Gemini 3 Pro has the larger documented context window: 2M, compared with 200K.
Last updated September 3, 2026
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