Agentic
Not comparable- Gemma 4 31B
- Not measured
- GPT-OSS 120B
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Gemma 4 31B vs GPT-OSS 120B
Updated August 17, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
Gemma 4 31B has the higher public score estimate, 60.15 versus 49.23, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.
2 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
Gemma 4 31B
Gemma 4 31B has the larger documented context window.
Confidence: documented
Show secondary and unsupported calls
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
Chat turn cost
1K fresh input + 500 output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
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. GPT-OSS 120B does not fit this workload in one request. Gemma 4 31B has no comparable published API token rate. GPT-OSS 120B has no comparable published API token rate.
Confidence: listed-rates
Repository review cost
50K fresh input + 3K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
6 Gemma 4 31B only
2 Shared
- Shared results
- 2
- Gemma 4 31B only
- 6
- GPT-OSS 120B only
- 0
- Like-for-like categories
- 0 / 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.
Coding
Not comparable- Gemma 4 31B
- 41.6
- GPT-OSS 120B
- Not measured
- Weighted basis
- 1 vs 0 rows
- Reading
- Not comparable
Reasoning
Not comparable- Gemma 4 31B
- Not measured
- GPT-OSS 120B
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Knowledge
Not comparable- Gemma 4 31B
- 52.9
- GPT-OSS 120B
- Not measured
- Weighted basis
- 3 vs 0 rows
- Reading
- Not comparable
Math
Not comparable- Gemma 4 31B
- Not measured
- GPT-OSS 120B
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Multilingual
Not comparable- Gemma 4 31B
- Not measured
- GPT-OSS 120B
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Multimodal
Not comparable- Gemma 4 31B
- 76.9
- GPT-OSS 120B
- Not measured
- Weighted basis
- 1 vs 0 rows
- Reading
- Not comparable
Instruction following
Not comparable- Gemma 4 31B
- Not measured
- GPT-OSS 120B
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
| Category | Gemma 4 31B | GPT-OSS 120B | Weighted basis | Reading |
|---|---|---|---|---|
| Agentic | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Coding | 41.6 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Reasoning | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Knowledge | 52.9 | Not measured | Not comparable3 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 |
| Multimodal | 76.9 | Not measured | Not comparable1 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.
A shared-evidence shape is not available.
BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.
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
- Gemma 4 31B
- Self-hosted; infrastructure cost varies
- Fits in one request
- GPT-OSS 120B
- Self-hosted; infrastructure cost varies
- Fits in one request
Gemma 4 31B has no comparable published API token rate. GPT-OSS 120B has no comparable published API token rate.
Repository review
50K fresh input + 3K output tokens
- Gemma 4 31B
- Self-hosted; infrastructure cost varies
- Fits in one request
- GPT-OSS 120B
- Self-hosted; infrastructure cost varies
- Fits in one request
Gemma 4 31B has no comparable published API token rate. GPT-OSS 120B has no comparable published API token rate.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- Gemma 4 31B
- Self-hosted; infrastructure cost varies
- Fits in one request
- Cached-input rate unavailable
- GPT-OSS 120B
- Self-hosted; infrastructure cost varies
- Does not fit in one request
- Cached-input rate unavailable
GPT-OSS 120B does not fit this workload in one request. Gemma 4 31B has no comparable published API token rate. GPT-OSS 120B has no comparable published API token rate.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationGemma 4 31BGPT-OSS 120B
Context window
Maximum documented context; output-token limits may be lower.
Gemma 4 31B
GPT-OSS 120B
128K
API model ID
Gemma 4 31B
gemma-4-31b-it
Google Gemma Gemini API guideGPT-OSS 120B
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
Gemma 4 31B
No comparable hosted API rate
GPT-OSS 120B
No comparable hosted API rate
Documented inputs
Gemma 4 31B
text, image
Google Gemma 4 model documentationGPT-OSS 120B
Not sourced
Documented outputs
Gemma 4 31B
GPT-OSS 120B
Not sourced
Provider availability
Gemma 4 31B
Generally Available · Gemini API, Google AI Studio, open weights
Google Gemma Gemini API guideGPT-OSS 120B
Not sourced
Reasoning profile
Gemma 4 31B
Reasoning
GPT-OSS 120B
Non-Reasoning
Weight access
Gemma 4 31B
Open Weight
GPT-OSS 120B
Open Weight
License
Gemma 4 31B
Open Weight
GPT-OSS 120B
Open Weight
Release date
Gemma 4 31B
2026-04-02
GPT-OSS 120B
2025-08-05
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
- Gemma 4 31B has the higher public score estimate, 60.15 versus 49.23, but the 90% score intervals overlap.
- Workload cost
- A complete comparable API-rate estimate is not available for both models.
- Context tradeoff
- Gemma 4 31B has the larger documented window (256K).
Run the same representative tasks against both endpoints before changing production traffic.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
Gemma 4 31B
API / mo$0
Self-host / mo$429
Break-even—
GPT-OSS 120B
API / mo$0
Self-host / moNot listed
Break-even—
Proprietary model — self-hosting not applicable.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence8 rows
Agentic
Gert Labs
Shared sourceGemma 4 31B35.26%GPT-OSS 120B29.61%Gemma 4 31B leads this result
Coding
SWE-Rebench
Gemma 4 31B41.6%SourceGPT-OSS 120B—Not directly comparable
React Native Evals
Shared sourceGemma 4 31B75.2%GPT-OSS 120B71.6%Gemma 4 31B leads this result
Knowledge
Multimodal
MMMU-Pro
Gemma 4 31B76.9%SourceGPT-OSS 120B—Not directly comparable
Frequently asked questions
Which is better, Gemma 4 31B or GPT-OSS 120B?
Gemma 4 31B has the higher public score estimate, 60.15 versus 49.23, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.
Which is better for coding, Gemma 4 31B or GPT-OSS 120B?
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, Gemma 4 31B or GPT-OSS 120B?
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, Gemma 4 31B or GPT-OSS 120B?
Both models do not have comparable published API token rates, so this page does not name a universal price winner.
Which has the larger context window, Gemma 4 31B or GPT-OSS 120B?
Gemma 4 31B has the larger documented context window: 256K, compared with 128K.
Related comparisons
Last updated August 17, 2026
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