Multimodal
Like-for-like- Claude Sonnet 5
- 88.3
- Gemini 3.1 Flash-Lite
- 73.2
- Weighted basis
- 1 vs 1 rows
- Reading
- Claude Sonnet 5 leads
Five or fewer confirmed AI changes, with original sources, on mornings when something changed.A free source-linked morning brief.
Start free briefUpdated August 14, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
Claude Sonnet 5 has the higher public score estimate, 64.78 versus 50.51, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
1 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 Flash-Lite
Gemini 3.1 Flash-Lite 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 Flash-Lite
Gemini 3.1 Flash-Lite 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 3.1 Flash-Lite
Gemini 3.1 Flash-Lite 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.
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 5 | Gemini 3.1 Flash-Lite | Weighted basis | Reading |
|---|---|---|---|---|
| Multimodal | 88.3 | 73.2 | Like-for-like1 vs 1 rows | Claude Sonnet 5 leads |
| Agentic | 81.9 | Not measured | Not comparable3 vs 0 rows | Not comparable |
| Coding | 76.7 | Not measured | Not comparable2 vs 0 rows | Not comparable |
| Reasoning | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Knowledge | 57.4 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Math | Not measured | Not measured | Not comparable0 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.
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 3.1 Flash-Lite has the lower modeled cost
Costs use the listed standard API rates.
50K fresh input + 3K output tokens
Gemini 3.1 Flash-Lite has the lower modeled cost
Costs use the listed standard API rates.
200K cached + 20K fresh input + 10K output tokens
Gemini 3.1 Flash-Lite has the lower modeled cost
Costs use the listed standard API rates.
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 5
Gemini 3.1 Flash-Lite
Claude Sonnet 5
claude-sonnet-5
Anthropic model overviewGemini 3.1 Flash-Lite
gemini-3.1-flash-lite
Google Gemini API pricingA missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Claude Sonnet 5
$0.2 per 1M cached input tokens
Claude API pricingGemini 3.1 Flash-Lite
$0.025 per 1M cached input tokens
Google Gemini API pricingClaude Sonnet 5
text, image
Anthropic model overviewGemini 3.1 Flash-Lite
Not sourced
Claude Sonnet 5
Gemini 3.1 Flash-Lite
Not sourced
Claude Sonnet 5
Generally Available · Claude API
Anthropic model overviewGemini 3.1 Flash-Lite
Not sourced
Claude Sonnet 5
Reasoning
Gemini 3.1 Flash-Lite
Non-Reasoning
Claude Sonnet 5
Proprietary
Gemini 3.1 Flash-Lite
Proprietary
Claude Sonnet 5
Proprietary
Gemini 3.1 Flash-Lite
Proprietary
Claude Sonnet 5
2026-06-30
Gemini 3.1 Flash-Lite
2026-03-03
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 3.0
Not directly comparable
Terminal-Bench 2.0
Not directly comparable
BrowseComp
Not directly comparable
HLE w/ tools
Not directly comparable
OSWorld-Verified
Not directly comparable
Gert Labs
Not directly comparable
SWE-bench Verified
Not directly comparable
SWE-bench Pro
Not directly comparable
SWE Multilingual
Not directly comparable
SWE Multimodal
Not directly comparable
Terminal-Bench 2.0
Not directly comparable
FrontierCode 1.1 Main
Not directly comparable
cursorBench32
Not directly comparable
APEX-SWE
Not directly comparable
EEBench
Not directly comparable
3DCodeBench
Not directly comparable
Vibe Code Bench
Not directly comparable
Claude Sonnet 5 has the higher public score estimate, 64.78 versus 50.51, 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 $0.007 on Claude Sonnet 5 and $0.001 on Gemini 3.1 Flash-Lite; repository review costs $0.13 and $0.017; the cache-heavy agent loop costs $0.18 and $0.025. Costs use the listed standard API rates.
Both models list the same context window, 1M.
Last updated August 14, 2026
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