GPT OSS 120B vs Qwen3 235B-A22B Instruct 2507 vs Qwen3.5 Flash
Qwen3.5 Flash comes out ahead, 73 to 58 and 57 on our weighted score, and it is the cheaper option too.
OpenAIGPT OSS 120B
58/100- ECI139.8
- Price$0.15 / $0.60
- Context131K
Alibaba (Qwen)Qwen3 235B-A22B Instruct 2507
57/100- ECI138.8
- Price$0.199 / $0.60
- Context262K
- Our pickAlibaba (Qwen)
Qwen3.5 Flash
73/100- ECI143.6
- Price$0.10 / $0.40
- Context1M
Qwen3.5 Flash is our pick
Qwen3.5 Flash is the better all-round choice, scoring 73/100 against GPT OSS 120B (58) and Qwen3 235B-A22B Instruct 2507 (57). It leads on capability, price, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityQwen3.5 FlashCapabilities Index (ECI): Qwen3.5 Flash 143.6 · GPT OSS 120B 139.8 · Qwen3 235B-A22B Instruct 2507 138.8
- Lowest priceQwen3.5 FlashQwen3.5 Flash $0.175 · GPT OSS 120B $0.263 · Qwen3 235B-A22B Instruct 2507 $0.299 per 1M tokens (3:1 blend)
- Longest contextQwen3.5 FlashQwen3.5 Flash 1,000,000 · Qwen3 235B-A22B Instruct 2507 262,144 · GPT OSS 120B 131,072 tokens
- Widest inputsQwen3.5 FlashGPT OSS 120B: Text · Qwen3 235B-A22B Instruct 2507: Text · Qwen3.5 Flash: Text, Images, Video
- Self-hostingGPT OSS 120B and Qwen3 235B-A22B Instruct 2507Publishes downloadable weights (Apache 2.0)
| Measure | Weight | GPT OSS 120B | Qwen3 235B-A22B Instruct 2507 | Qwen3.5 Flash |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 64 | 63 | 69 |
| Price | 25% | 74 | 72 | 82 |
| Inputs & features | 15% | 35 | 25 | 80 |
| Context window | 10% | 25 | 37 | 60 |
| Overall | 100% | 58/100 | 57/100 | 73/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GPT OSS 120BOpenAI | Qwen3 235B-A22B Instruct 2507Alibaba (Qwen) | Qwen3.5 FlashAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 139.8 | 138.8 | 143.6 (best) |
| ECI rank | #114 of 165 | #118 of 165 | #95 of 165 (best) |
| GPQA DiamondGraduate-level science questions | 75.8% | — | 82.3% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | — | — | 18.3% |
| OTIS Mock AIME 2024–2025Competition mathematics | 88.9% (best) | — | 84.4% |
| SimpleQA VerifiedShort factual questions | — | — | 20.3% |
| Price per million tokens | |||
| Input | $0.15 | $0.199 | $0.10 (best) |
| Output | $0.60 | $0.60 | $0.40 (best) |
| Cached input | — | — | $0.01 |
| Blended (3:1) | $0.263 | $0.299 | $0.175 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 65 providers | Median of 23 providers | Official Alibaba API |
| Limits | |||
| Context window | 131,072 tokens | 262,144 tokens | 1,000,000 tokens (best) |
| Max output | 32,768 tokens | 16,384 tokens | 65,536 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | Yes |
| Reasoning | Yes | No | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | Open | OpenApache 2.0 | Proprietary |
| API model ID | — | — | qwen3.5-flash |
| API providers | 67 (best) | 25 | 9 |
| Released | Aug 5, 2025 | Jul 21, 2025 | Feb 23, 2026 |
| Knowledge cutoff | 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.
- GPT OSS 120B$2.70
- Qwen3 235B-A22B Instruct 2507$3.19
- Qwen3.5 Flash$1.80
Which should you choose?
Which is better: GPT OSS 120B, Qwen3 235B-A22B Instruct 2507 or Qwen3.5 Flash?
Qwen3.5 Flash is the better all-round choice, scoring 73/100 against GPT OSS 120B (58) and Qwen3 235B-A22B Instruct 2507 (57). It leads on capability, price, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, GPT OSS 120B, Qwen3 235B-A22B Instruct 2507 or Qwen3.5 Flash?
Qwen3.5 Flash is cheaper at $0.10 input / $0.40 output per million tokens (official Alibaba API price). 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 $0.175 per million tokens for Qwen3.5 Flash versus $0.263 for GPT OSS 120B (1.5× as much) and $0.299 for Qwen3 235B-A22B Instruct 2507 (1.7× as much).
Which scores higher on benchmarks?
Qwen3.5 Flash scores higher on the Capabilities Index (ECI): Qwen3.5 Flash 143.6 (#95 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 (141.4–145.0 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 GPT OSS 120B, Qwen3 235B-A22B Instruct 2507 and Qwen3.5 Flash yet, so there is no like-for-like coding score. On overall capability, Qwen3.5 Flash 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?
Qwen3.5 Flash 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: GPT OSS 120B up to 32,768, Qwen3 235B-A22B Instruct 2507 up to 16,384, Qwen3.5 Flash up to 65,536 tokens.
Which can read images, PDFs, audio or video?
GPT OSS 120B accepts text; Qwen3 235B-A22B Instruct 2507 accepts text; Qwen3.5 Flash accepts text, images and video. Qwen3.5 Flash handles the widest range of inputs.
Are any of these open source?
GPT OSS 120B and Qwen3 235B-A22B Instruct 2507 publishes its weights (Apache 2.0) and can be self-hosted; Qwen3.5 Flash is proprietary.
Which is newer?
Qwen3.5 Flash is the newest, released Feb 23, 2026. GPT OSS 120B came out Aug 5, 2025; Qwen3 235B-A22B Instruct 2507 came out Jul 21, 2025. Knowledge cutoff: 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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