Qwen3 235B-A22B Instruct 2507 vs Qwen3.5 Flash vs GPT OSS 120B
Qwen3.5 Flash comes out ahead, 73 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 pickAlibaba (Qwen)
Qwen3.5 Flash
73/100- ECI143.6
- Price$0.10 / $0.40
- Context1M
OpenAIGPT OSS 120B
58/100- ECI139.8
- Price$0.15 / $0.60
- Context131K
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 FlashQwen3 235B-A22B Instruct 2507: Text · Qwen3.5 Flash: Text, Images, Video · GPT OSS 120B: Text
- Self-hostingQwen3 235B-A22B Instruct 2507 and GPT OSS 120BPublishes downloadable weights (Apache 2.0)
| Measure | Weight | Qwen3 235B-A22B Instruct 2507 | Qwen3.5 Flash | GPT OSS 120B |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 63 | 69 | 64 |
| Price | 25% | 72 | 82 | 74 |
| Inputs & features | 15% | 25 | 80 | 35 |
| Context window | 10% | 37 | 60 | 25 |
| Overall | 100% | 57/100 | 73/100 | 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) | Qwen3.5 FlashAlibaba (Qwen) | GPT OSS 120BOpenAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 138.8 | 143.6 (best) | 139.8 |
| ECI rank | #118 of 165 | #95 of 165 (best) | #114 of 165 |
| GPQA DiamondGraduate-level science questions | — | 82.3% (best) | 75.8% |
| FrontierMath Tiers 1–3Research-level mathematics | — | 18.3% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 84.4% | 88.9% (best) |
| SimpleQA VerifiedShort factual questions | — | 20.3% | — |
| Price per million tokens | |||
| Input | $0.199 | $0.10 (best) | $0.15 |
| Output | $0.60 | $0.40 (best) | $0.60 |
| Cached input | — | $0.01 | — |
| Blended (3:1) | $0.299 | $0.175 (best) | $0.263 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 23 providers | Official Alibaba API | Median of 65 providers |
| Limits | |||
| Context window | 262,144 tokens | 1,000,000 tokens (best) | 131,072 tokens |
| Max output | 16,384 tokens | 65,536 tokens (best) | 32,768 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | Yes | No |
| Reasoning | No | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | OpenApache 2.0 | Proprietary | Open |
| API model ID | — | qwen3.5-flash | — |
| API providers | 25 | 9 | 67 (best) |
| Released | Jul 21, 2025 | Feb 23, 2026 | Aug 5, 2025 |
| 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.
- Qwen3 235B-A22B Instruct 2507$3.19
- Qwen3.5 Flash$1.80
- GPT OSS 120B$2.70
Which should you choose?
Which is better: Qwen3 235B-A22B Instruct 2507, Qwen3.5 Flash or GPT OSS 120B?
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, Qwen3 235B-A22B Instruct 2507, Qwen3.5 Flash or GPT OSS 120B?
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 Qwen3 235B-A22B Instruct 2507, Qwen3.5 Flash and GPT OSS 120B 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: Qwen3 235B-A22B Instruct 2507 up to 16,384, Qwen3.5 Flash up to 65,536, GPT OSS 120B up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Qwen3 235B-A22B Instruct 2507 accepts text; Qwen3.5 Flash accepts text, images and video; GPT OSS 120B accepts text. Qwen3.5 Flash handles the widest range of inputs.
Are any of these open source?
Qwen3 235B-A22B Instruct 2507 and GPT OSS 120B 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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