Multimodal
Like-for-like- Claude Sonnet 4.6
- 77.4
- Gemini 3.7 Flash
- 88.7
- Weighted basis
- 1 vs 1 rows
- Reading
- Gemini 3.7 Flash leads
Claude Sonnet 4.6 vs Gemini 3.7 Flash
Updated August 13, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
3 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.
Which one for your work
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.
Long documents
Prompts that approach the documented context limit
Gemini 3.7 Flash
Gemini 3.7 Flash has the larger documented context window.
Confidence: documented
Chat turn cost
1K fresh input + 500 output tokens
Gemini 3.7 Flash
Gemini 3.7 Flash has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Show secondary and unsupported calls
Repository review cost
50K fresh input + 3K output tokens
Gemini 3.7 Flash
Gemini 3.7 Flash has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
Cache-heavy agent loop cost
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 3.7 Flash has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
19 Claude Sonnet 4.6 only
3 Shared
12 Gemini 3.7 Flash only
- Shared results
- 3
- Claude Sonnet 4.6 only
- 19
- Gemini 3.7 Flash only
- 12
- Like-for-like categories
- 1 / 8
Category results, on a stated basis
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.
Agentic
Not comparable- Claude Sonnet 4.6
- 65.2
- Gemini 3.7 Flash
- Not measured
- Weighted basis
- 2 vs 0 rows
- Reading
- Not comparable
Coding
Not comparable- Claude Sonnet 4.6
- 69.1
- Gemini 3.7 Flash
- Not measured
- Weighted basis
- 2 vs 0 rows
- Reading
- Not comparable
Reasoning
Not comparable- Claude Sonnet 4.6
- Not measured
- Gemini 3.7 Flash
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Knowledge
Not comparable- Claude Sonnet 4.6
- 66.0
- Gemini 3.7 Flash
- Not measured
- Weighted basis
- 4 vs 0 rows
- Reading
- Not comparable
Math
Not comparable- Claude Sonnet 4.6
- 26.4
- Gemini 3.7 Flash
- Not measured
- Weighted basis
- 2 vs 0 rows
- Reading
- Not comparable
Multilingual
Not comparable- Claude Sonnet 4.6
- Not measured
- Gemini 3.7 Flash
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Instruction following
Not comparable- Claude Sonnet 4.6
- Not measured
- Gemini 3.7 Flash
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
| Category | Claude Sonnet 4.6 | Gemini 3.7 Flash | Weighted basis | Reading |
|---|---|---|---|---|
| Multimodal | 77.4 | 88.7 | Like-for-like1 vs 1 rows | Gemini 3.7 Flash leads |
| 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 | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Knowledge | 66.0 | Not measured | Not comparable4 vs 0 rows | Not comparable |
| Math | 26.4 | Not measured | Not comparable2 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 |
Shape of the matched evidence
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
Claude Sonnet 4.6: 77.4%Gemini 3.7 Flash: 88.7%Normalized gap 11.3Claude Sonnet 4.6 source Gemini 3.7 Flash source
What each workload costs
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.
Chat turn
1K fresh input + 500 output tokens
- Claude Sonnet 4.6
- $0.0105
- Fits in one request
- Gemini 3.7 Flash
- $0.00262
- Fits in one request
Gemini 3.7 Flash has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- Claude Sonnet 4.6
- $0.195
- Fits in one request
- Gemini 3.7 Flash
- $0.04875
- Fits in one request
Gemini 3.7 Flash has the lower modeled cost
Costs use the listed standard API rates.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Claude Sonnet 4.6
- $0.81
- Does not fit in one request
- Cached input priced at the published list-input rate
- Gemini 3.7 Flash
- $0.2025
- Fits in one request
- Cached input priced at the published list-input rate
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 3.7 Flash has no published cached-input rate, so cached tokens use its listed input rate.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationClaude Sonnet 4.6Gemini 3.7 Flash
Context window
Maximum documented context; output-token limits may be lower.
Claude Sonnet 4.6
200K
Gemini 3.7 Flash
API model ID
Claude Sonnet 4.6
Not sourced
Gemini 3.7 Flash
gemini-3.7-flash
Google Gemini 3.7 Flash model documentationCached-input rate
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 3.7 Flash
Not published
Google: Introducing Gemini 3.7 FlashDocumented inputs
Claude Sonnet 4.6
Not sourced
Gemini 3.7 Flash
text, image, video, audio, pdf
Google Gemini 3.7 Flash model documentationDocumented outputs
Claude Sonnet 4.6
Not sourced
Gemini 3.7 Flash
Provider availability
Claude Sonnet 4.6
Not sourced
Gemini 3.7 Flash
Generally Available · Gemini API, Google AI Studio, Google Antigravity, Gemini Enterprise Agent Platform, Gemini Enterprise, Gemini app via Spark
Google Gemini 3.7 Flash launchReasoning profile
Claude Sonnet 4.6
Non-Reasoning
Gemini 3.7 Flash
Reasoning
Weight access
Claude Sonnet 4.6
Proprietary
Gemini 3.7 Flash
Proprietary
License
Claude Sonnet 4.6
Proprietary
Gemini 3.7 Flash
Proprietary
Release date
Claude Sonnet 4.6
2026-02-01
Gemini 3.7 Flash
2026-08-13
If you already use one of these models
- Deployment change
- The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
- Quality signal
- At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
- Workload cost
- Repository review: $0.195 vs $0.04875. Cache-heavy agent loop: $0.81 vs $0.2025.
- Context tradeoff
- Gemini 3.7 Flash has the larger documented window (1M).
Run the same representative tasks against both endpoints before changing production traffic.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence34 rows
Agentic
Terminal-Bench 2.0
Claude Sonnet 4.659.1%SourceGemini 3.7 Flash—Not directly comparable
OSWorld-Verified
Claude Sonnet 4.672.1%SourceGemini 3.7 Flash—Not directly comparable
Claw-Eval
Claude Sonnet 4.667.8%SourceGemini 3.7 Flash—Not directly comparable
CyberGym
Claude Sonnet 4.665.2%SourceGemini 3.7 Flash—Not directly comparable
Gert Labs
Claude Sonnet 4.662.92%SourceGemini 3.7 Flash—Not directly comparable
OSWorld 2.0
Claude Sonnet 4.68.3%SourceGemini 3.7 Flash47.9%SourceGemini 3.7 Flash leads this result
JobBench
Claude Sonnet 4.636.9%SourceGemini 3.7 Flash—Not directly comparable
Terminal-Bench 2.1
Claude Sonnet 4.6—Gemini 3.7 Flash85.8%SourceNot directly comparable
Terminal-Bench 3.0
Claude Sonnet 4.6—Gemini 3.7 Flash14.9%SourceNot directly comparable
AutomationBench
Claude Sonnet 4.6—Gemini 3.7 Flash30.4%SourceNot directly comparable
Agents' Last Exam
Claude Sonnet 4.6—Gemini 3.7 Flash26.3%SourceNot directly comparable
Coding
SWE-bench Verified
Claude Sonnet 4.679.6%SourceGemini 3.7 Flash—Not directly comparable
SWE-Rebench
Claude Sonnet 4.660.7%SourceGemini 3.7 Flash—Not directly comparable
React Native Evals
Claude Sonnet 4.680.6%SourceGemini 3.7 Flash—Not directly comparable
Vibe Code Bench
Claude Sonnet 4.651.48%SourceGemini 3.7 Flash—Not directly comparable
cursorBench31
Claude Sonnet 4.648.8%SourceGemini 3.7 Flash—Not directly comparable
FrontierCode 1.1 Main
Claude Sonnet 4.624.3%SourceGemini 3.7 Flash43.6%SourceGemini 3.7 Flash leads this result
EEBench
Claude Sonnet 4.620.4%SourceGemini 3.7 Flash—Not directly comparable
CADGenBench Generation
Claude Sonnet 4.622.1%SourceGemini 3.7 Flash—Not directly comparable
deepSwe
Claude Sonnet 4.6—Gemini 3.7 Flash65.3%SourceNot directly comparable
Terminal-Bench 2.1
Claude Sonnet 4.6—Gemini 3.7 Flash85.8%SourceNot directly comparable
Reasoning
GDM-MRCR v2 128K average
Claude Sonnet 4.6—Gemini 3.7 Flash97%SourceNot directly comparable
Knowledge
GPQA
Claude Sonnet 4.689.9%SourceGemini 3.7 Flash—Not directly comparable
SuperGPQA
Claude Sonnet 4.695%SourceGemini 3.7 Flash—Not directly comparable
MMLU-Pro
Claude Sonnet 4.679.2%SourceGemini 3.7 Flash—Not directly comparable
HLE
Claude Sonnet 4.649%SourceGemini 3.7 Flash—Not directly comparable
BioMysteryBench (human-solvable)
Claude Sonnet 4.6—Gemini 3.7 Flash87.1%SourceNot directly comparable
BioMysteryBench (human-difficult)
Claude Sonnet 4.6—Gemini 3.7 Flash43.5%SourceNot directly comparable
Math
Multimodal
CharXiv
Claude Sonnet 4.677.4%SourceGemini 3.7 Flash88.7%SourceGemini 3.7 Flash leads this result
GDP.pdf (no tools)
Claude Sonnet 4.6—Gemini 3.7 Flash34.0%SourceNot directly comparable
CharXiv w/o tools
Claude Sonnet 4.6—Gemini 3.7 Flash84.5%SourceNot directly comparable
LVBench
Claude Sonnet 4.6—Gemini 3.7 Flash85.4%SourceNot directly comparable
Frequently asked questions
Which is better, Claude Sonnet 4.6 or Gemini 3.7 Flash?
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. The page therefore keeps the decision tied to the specific documented workload.
Which is better for coding, Claude Sonnet 4.6 or Gemini 3.7 Flash?
The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.
Which is better for agentic tasks, Claude Sonnet 4.6 or Gemini 3.7 Flash?
The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.
Which costs less, Claude Sonnet 4.6 or Gemini 3.7 Flash?
For the stated presets, chat costs $0.0105 on Claude Sonnet 4.6 and $0.00263 on Gemini 3.7 Flash; repository review costs $0.195 and $0.04875; the cache-heavy agent loop costs $0.81 and $0.2025. 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 3.7 Flash has no published cached-input rate, so cached tokens use its listed input rate.
Which has the larger context window, Claude Sonnet 4.6 or Gemini 3.7 Flash?
Gemini 3.7 Flash has the larger documented context window: 1M, compared with 200K.
Related comparisons
Last updated August 13, 2026
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