Qwen3 235B-A22B Instruct 2507 vs Llama 4 Maverick 17B Instruct vs GPT OSS 120B
GPT OSS 120B comes out ahead, 61 to 58 and 58 on our weighted score, and it is the cheaper option too.
Alibaba (Qwen)Qwen3 235B-A22B Instruct 2507
58/100- ECI138.9
- Price$0.15 / $0.75
- Context262K
MetaLlama 4 Maverick 17B Instruct
58/100- ECI132.2
- Price$0.321 / $0.91
- Context1M
- Our pick
OpenAIGPT OSS 120B
61/100- ECI140.0
- Price$0.15 / $0.60
- Context131K
GPT OSS 120B is our pick
GPT OSS 120B is the better all-round choice, scoring 61/100 against Qwen3 235B-A22B Instruct 2507 (58) and Llama 4 Maverick 17B Instruct (58). It leads on price. Llama 4 Maverick 17B Instruct wins on inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGPT OSS 120BCapabilities Index (ECI): GPT OSS 120B 140.0 · Qwen3 235B-A22B Instruct 2507 138.9 · Llama 4 Maverick 17B Instruct 132.2
- Lowest priceGPT OSS 120BGPT OSS 120B $0.263 · Qwen3 235B-A22B Instruct 2507 $0.30 · Llama 4 Maverick 17B Instruct $0.468 per 1M tokens (3:1 blend)
- Longest contextLlama 4 Maverick 17B InstructLlama 4 Maverick 17B Instruct 1,000,000 · Qwen3 235B-A22B Instruct 2507 262,144 · GPT OSS 120B 131,072 tokens
- Widest inputsLlama 4 Maverick 17B InstructQwen3 235B-A22B Instruct 2507: Text · Llama 4 Maverick 17B Instruct: 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 | Llama 4 Maverick 17B Instruct | GPT OSS 120B |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 64 | 56 | 65 |
| Price | 25% | 75 | 66 | 77 |
| Inputs & features | 15% | 25 | 50 | 45 |
| Context window | 10% | 37 | 60 | 24 |
| Overall | 100% | 58/100 | 58/100 | 61/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Qwen3 235B-A22B Instruct 2507Alibaba (Qwen) | Llama 4 Maverick 17B InstructMeta | GPT OSS 120BOpenAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 138.9 | 132.2 | 140.0 (best) |
| ECI rank | #105 of 148 | #122 of 148 | #99 of 148 (best) |
| GPQA DiamondGraduate-level science questions | — | 67.0% | 75.8% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 20.6% | 88.9% (best) |
| Price per million tokens | |||
| Input | $0.15 (best) | $0.321 | $0.15 (best) |
| Output | $0.75 | $0.91 | $0.60 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.30 | $0.468 | $0.263 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 11 providers | Median of 6 providers | Median of 36 providers |
| Limits | |||
| Context window | 262,144 tokens | 1,000,000 tokens (best) | 131,072 tokens |
| Max output | 16,384 tokens | 16,384 tokens | 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 | No | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | OpenApache 2.0 | Open | Open |
| API model ID | — | — | — |
| API providers | 11 | 6 | 39 (best) |
| Released | Jul 21, 2025 | Apr 5, 2025 | Aug 5, 2025 |
| Knowledge cutoff | — | Aug 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$3.00
- Llama 4 Maverick 17B Instruct$5.03
- GPT OSS 120B$2.70
Which should you choose?
Which is better: Qwen3 235B-A22B Instruct 2507, Llama 4 Maverick 17B Instruct or GPT OSS 120B?
GPT OSS 120B is the better all-round choice, scoring 61/100 against Qwen3 235B-A22B Instruct 2507 (58) and Llama 4 Maverick 17B Instruct (58). It leads on price. Llama 4 Maverick 17B Instruct wins on inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Qwen3 235B-A22B Instruct 2507, Llama 4 Maverick 17B Instruct or GPT OSS 120B?
GPT OSS 120B is cheaper at $0.15 input / $0.60 output per million tokens (median across 36 API providers). Qwen3 235B-A22B Instruct 2507 costs $0.15 input / $0.75 output per million tokens (median across 11 API providers); Llama 4 Maverick 17B Instruct costs $0.321 input / $0.91 output per million tokens (median across 6 API providers). At a typical mix of three input tokens to one output token, that is $0.263 per million tokens for GPT OSS 120B versus $0.30 for Qwen3 235B-A22B Instruct 2507 (1.1× as much) and $0.468 for Llama 4 Maverick 17B Instruct (1.8× as much).
Which scores higher on benchmarks?
GPT OSS 120B scores higher on the Capabilities Index (ECI): GPT OSS 120B 140.0 (#99 of 148), Qwen3 235B-A22B Instruct 2507 138.9 (#105 of 148) and Llama 4 Maverick 17B Instruct 132.2 (#122 of 148). The confidence ranges of the top two overlap (135.3–142.3 vs 135.8–140.6), 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, Llama 4 Maverick 17B Instruct and GPT OSS 120B yet, so there is no like-for-like coding score. On overall capability, GPT OSS 120B 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?
Llama 4 Maverick 17B Instruct has the largest context window at 1,000,000 tokens, against 262,144 for Qwen3 235B-A22B Instruct 2507 and 131,072 for GPT OSS 120B. Maximum output per response: Qwen3 235B-A22B Instruct 2507 up to 16,384, Llama 4 Maverick 17B Instruct up to 16,384, GPT OSS 120B up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Qwen3 235B-A22B Instruct 2507 accepts text; Llama 4 Maverick 17B Instruct accepts text and images; GPT OSS 120B accepts text. Llama 4 Maverick 17B Instruct 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?
GPT OSS 120B is the newest, released Aug 5, 2025. Qwen3 235B-A22B Instruct 2507 came out Jul 21, 2025; Llama 4 Maverick 17B Instruct came out Apr 5, 2025. Knowledge cutoff: Llama 4 Maverick 17B Instruct Aug 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 Oct 4, 2026.
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