Qwen3 235B-A22B Instruct 2507 vs Gemma 4 31B IT vs GPT OSS 120B
Gemma 4 31B IT comes out ahead, 68 to 58 and 57 on our weighted score, and it is the cheaper option too.
Alibaba (Qwen)Qwen3 235B-A22B Instruct 2507
57/100- ECI138.8
- Price$0.199 / $0.60
- Context262K
- Our pick
GoogleGemma 4 31B IT
68/100- ECI143.1
- Price$0.14 / $0.40
- Context262K
OpenAIGPT OSS 120B
58/100- ECI139.8
- Price$0.15 / $0.60
- Context131K
Gemma 4 31B IT is our pick
Gemma 4 31B IT is the better all-round choice, scoring 68/100 against GPT OSS 120B (58) and Qwen3 235B-A22B Instruct 2507 (57). It leads on capability, price and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGemma 4 31B ITCapabilities Index (ECI): Gemma 4 31B IT 143.1 · GPT OSS 120B 139.8 · Qwen3 235B-A22B Instruct 2507 138.8
- Lowest priceGemma 4 31B ITGemma 4 31B IT $0.205 · GPT OSS 120B $0.263 · Qwen3 235B-A22B Instruct 2507 $0.299 per 1M tokens (3:1 blend)
- Longest contextQwen3 235B-A22B Instruct 2507 and Gemma 4 31B ITQwen3 235B-A22B Instruct 2507 262,144 · Gemma 4 31B IT 262,144 · GPT OSS 120B 131,072 tokens
- Widest inputsGemma 4 31B ITQwen3 235B-A22B Instruct 2507: Text · Gemma 4 31B IT: Text, Images · GPT OSS 120B: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Qwen3 235B-A22B Instruct 2507 | Gemma 4 31B IT | GPT OSS 120B |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 63 | 68 | 64 |
| Price | 25% | 72 | 79 | 74 |
| Inputs & features | 15% | 25 | 70 | 35 |
| Context window | 10% | 37 | 37 | 25 |
| Overall | 100% | 57/100 | 68/100 | 58/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Qwen3 235B-A22B Instruct 2507Alibaba (Qwen) | Gemma 4 31B ITGoogle | GPT OSS 120BOpenAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 138.8 | 143.1 (best) | 139.8 |
| ECI rank | #118 of 165 | #96 of 165 (best) | #114 of 165 |
| GPQA DiamondGraduate-level science questions | — | 75.8% | 75.8% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 73.3% | 88.9% (best) |
| SimpleQA VerifiedShort factual questions | — | 10.4% | — |
| Price per million tokens | |||
| Input | $0.199 | $0.14 (best) | $0.15 |
| Output | $0.60 | $0.40 (best) | $0.60 |
| Cached input | — | — | — |
| Blended (3:1) | $0.299 | $0.205 (best) | $0.263 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 23 providers | Median of 36 providers | Median of 65 providers |
| Limits | |||
| Context window | 262,144 tokens (best) | 262,144 tokens (best) | 131,072 tokens |
| Max output | 16,384 tokens | 32,768 tokens (best) | 32,768 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | OpenApache 2.0 | Open | Open |
| API model ID | — | gemma-4-31b-it | — |
| API providers | 25 | 46 | 67 (best) |
| Released | Jul 21, 2025 | Apr 2, 2026 | Aug 5, 2025 |
| Knowledge cutoff | — | Jan 2025 | Jun 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Qwen3 235B-A22B Instruct 2507$3.19
- Gemma 4 31B IT$2.20
- GPT OSS 120B$2.70
Which should you choose?
Which is better: Qwen3 235B-A22B Instruct 2507, Gemma 4 31B IT or GPT OSS 120B?
Gemma 4 31B IT is the better all-round choice, scoring 68/100 against GPT OSS 120B (58) and Qwen3 235B-A22B Instruct 2507 (57). It leads on capability, price and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Qwen3 235B-A22B Instruct 2507, Gemma 4 31B IT or GPT OSS 120B?
Gemma 4 31B IT is cheaper at $0.14 input / $0.40 output per million tokens (median across 36 API providers). GPT OSS 120B costs $0.15 input / $0.60 output per million tokens (median across 65 API providers); Qwen3 235B-A22B Instruct 2507 costs $0.199 input / $0.60 output per million tokens (median across 23 API providers). At a typical mix of three input tokens to one output token, that is $0.205 per million tokens for Gemma 4 31B IT versus $0.263 for GPT OSS 120B (1.3× as much) and $0.299 for Qwen3 235B-A22B Instruct 2507 (1.5× as much).
Which scores higher on benchmarks?
Gemma 4 31B IT scores higher on the Capabilities Index (ECI): Gemma 4 31B IT 143.1 (#96 of 165), GPT OSS 120B 139.8 (#114 of 165) and Qwen3 235B-A22B Instruct 2507 138.8 (#118 of 165). The confidence ranges of the top two overlap (140.8–145.9 vs 135.6–142.2), so treat the gap as small.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3 235B-A22B Instruct 2507, Gemma 4 31B IT and GPT OSS 120B yet, so there is no like-for-like coding score. On overall capability, Gemma 4 31B IT leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.
Which has the bigger context window?
Qwen3 235B-A22B Instruct 2507 and Gemma 4 31B IT have the largest context windows (262,144 and 262,144 tokens), against 131,072 for GPT OSS 120B. Maximum output per response: Qwen3 235B-A22B Instruct 2507 up to 16,384, Gemma 4 31B IT up to 32,768, GPT OSS 120B up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Qwen3 235B-A22B Instruct 2507 accepts text; Gemma 4 31B IT accepts text and images; GPT OSS 120B accepts text. Gemma 4 31B IT handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights (Apache 2.0), so you can self-host them.
Which is newer?
Gemma 4 31B IT is the newest, released Apr 2, 2026. GPT OSS 120B came out Aug 5, 2025; Qwen3 235B-A22B Instruct 2507 came out Jul 21, 2025. Knowledge cutoff: Gemma 4 31B IT Jan 2025, GPT OSS 120B Jun 2024.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Nov 2, 2026.
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