Math
Like-for-like- Gemini 3.1 Pro
- 31.8
- GPT-5.4 mini
- 21.7
- Weighted basis
- 2 vs 2 rows
- Reading
- Gemini 3.1 Pro leads
Model comparison
Updated July 30, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
GPT-5.4 mini has the higher public score estimate, 55.79 versus 54.66, 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
GPT-5.4 mini
GPT-5.4 mini 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
GPT-5.4 mini
GPT-5.4 mini 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
GPT-5.4 mini
GPT-5.4 mini 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
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 | Gemini 3.1 Pro | GPT-5.4 mini | Weighted basis | Reading |
|---|---|---|---|---|
| Math | 31.8 | 21.7 | Like-for-like2 vs 2 rows | Gemini 3.1 Pro leads |
| Multimodal | 82.6 | 76.6 | Directional only2 vs 1 rows | Directional only |
| Agentic | Not measured | 65.7 | Not comparable0 vs 2 rows | Not comparable |
| Coding | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Reasoning | 77.1 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Knowledge | Not measured | 47.8 | Not comparable0 vs 2 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
MMMU-Pro
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
GPT-5.4 mini has the lower modeled cost
Costs use the listed standard API rates.
50K fresh input + 3K output tokens
GPT-5.4 mini has the lower modeled cost
Costs use the listed standard API rates.
200K cached + 20K fresh input + 10K output tokens
GPT-5.4 mini 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.
Gemini 3.1 Pro
GPT-5.4 mini
Gemini 3.1 Pro
gemini-3.1-pro-preview
Google Gemini 3.1 Pro Preview model documentationGPT-5.4 mini
gpt-5.4-mini
OpenAI GPT-5.4 mini model documentationA 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 pricingGPT-5.4 mini
$0.075 per 1M cached input tokens
OpenAI pricingGemini 3.1 Pro
text, image, video, audio, pdf
Google Gemini 3.1 Pro Preview model documentationGPT-5.4 mini
text, image
OpenAI model catalogGemini 3.1 Pro
GPT-5.4 mini
Gemini 3.1 Pro
Preview · Gemini API, Google AI Studio
Google Gemini model catalogGPT-5.4 mini
Generally Available · OpenAI Responses API
OpenAI model catalogGemini 3.1 Pro
Reasoning
GPT-5.4 mini
Reasoning
Gemini 3.1 Pro
Proprietary
GPT-5.4 mini
Proprietary
Gemini 3.1 Pro
Proprietary
GPT-5.4 mini
Proprietary
Gemini 3.1 Pro
2026-02-19
GPT-5.4 mini
2026-03-17
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
Not directly comparable
DeepSearchQA
Not directly comparable
τ²-bench results
Gemini 3.1 Pro leads this result
Gert Labs
Not directly comparable
ResearchClawBench
Not directly comparable
Terminal-Bench 2.0
Not directly comparable
OSWorld-Verified
Not directly comparable
MCP Atlas
Not directly comparable
Toolathlon
Not directly comparable
LiveCodeBench Pro
Not directly comparable
React Native Evals
Not directly comparable
Vibe Code Bench
Shared sourceGPT-5.4 mini leads this result
FrontierCode 1.1 Main
Not directly comparable
GPQA-D
Not directly comparable
HLE w/o tools
Gemini 3.1 Pro leads this result
HealthBench Hard
Not directly comparable
MedXpertQA (Text)
Not directly comparable
GPQA
Not directly comparable
HLE
Not directly comparable
FrontierMath v2 (Tiers 1-3)
Shared sourceGemini 3.1 Pro leads this result
FrontierMath v2 (Tier 4)
Shared sourceGemini 3.1 Pro leads this result
MMMU-Pro
Gemini 3.1 Pro leads this result
CharXiv
Not directly comparable
ERQA
Not directly comparable
SimpleVQA
Not directly comparable
ScreenSpot Pro
Not directly comparable
ZeroBench
Not directly comparable
MedXpertQA (MM)
Not directly comparable
MMMU-Pro w/ Python
Not directly comparable
GPT-5.4 mini has the higher public score estimate, 55.79 versus 54.66, 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 $0.003 on GPT-5.4 mini; repository review costs $0.136 and $0.051; the cache-heavy agent loop costs $0.2 and $0.075. Costs use the listed standard API rates.
Gemini 3.1 Pro has the larger documented context window: 1M, compared with 400K.
Last updated July 30, 2026
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