GPT OSS 20B vs Qwen3 235B-A22B Instruct 2507 vs Qwen3.5 9B
Qwen3.5 9B comes out ahead, 72 to 64 and 58 on our weighted score, and it is the cheaper option too.
OpenAIGPT OSS 20B
64/100- ECI137.8
- Price$0.07 / $0.295
- Context131K
Alibaba (Qwen)Qwen3 235B-A22B Instruct 2507
58/100- ECI138.9
- Price$0.15 / $0.75
- Context262K
- Our pickAlibaba (Qwen)
Qwen3.5 9B
72/100- ECI139.5
- Price$0.10 / $0.15
- Context262K
Qwen3.5 9B is our pick
Qwen3.5 9B is the better all-round choice, scoring 72/100 against GPT OSS 20B (64) and Qwen3 235B-A22B Instruct 2507 (58). It leads on price and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityQwen3.5 9BCapabilities Index (ECI): Qwen3.5 9B 139.5 · Qwen3 235B-A22B Instruct 2507 138.9 · GPT OSS 20B 137.8
- Lowest priceQwen3.5 9BQwen3.5 9B $0.113 · GPT OSS 20B $0.126 · Qwen3 235B-A22B Instruct 2507 $0.30 per 1M tokens (3:1 blend)
- Longest contextQwen3 235B-A22B Instruct 2507 and Qwen3.5 9BQwen3 235B-A22B Instruct 2507 262,144 · Qwen3.5 9B 262,144 · GPT OSS 20B 131,072 tokens
- Widest inputsQwen3.5 9BGPT OSS 20B: Text · Qwen3 235B-A22B Instruct 2507: Text · Qwen3.5 9B: Text, Images, Video
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | GPT OSS 20B | Qwen3 235B-A22B Instruct 2507 | Qwen3.5 9B |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 63 | 64 | 65 |
| Price | 25% | 92 | 75 | 95 |
| Inputs & features | 15% | 45 | 25 | 80 |
| Context window | 10% | 24 | 37 | 37 |
| Overall | 100% | 64/100 | 58/100 | 72/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GPT OSS 20BOpenAI | Qwen3 235B-A22B Instruct 2507Alibaba (Qwen) | Qwen3.5 9BAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 137.8 | 138.9 | 139.5 (best) |
| ECI rank | #108 of 148 | #105 of 148 | #101 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 60.8% | — | 79.0% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 65.3% (best) | — | 61.7% |
| Price per million tokens | |||
| Input | $0.07 (best) | $0.15 | $0.10 |
| Output | $0.295 | $0.75 | $0.15 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.126 | $0.30 | $0.113 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 18 providers | Median of 11 providers | Median of 14 providers |
| Limits | |||
| Context window | 131,072 tokens | 262,144 tokens (best) | 262,144 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 | Yes | No | Yes |
| Availability | |||
| Weights | Open | OpenApache 2.0 | Open |
| API model ID | — | — | — |
| API providers | 19 (best) | 11 | 15 |
| Released | Aug 5, 2025 | Jul 21, 2025 | Feb 23, 2026 |
| Knowledge cutoff | — | — | — |
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 20B$1.29
- Qwen3 235B-A22B Instruct 2507$3.00
- Qwen3.5 9B$1.30
Which should you choose?
Which is better: GPT OSS 20B, Qwen3 235B-A22B Instruct 2507 or Qwen3.5 9B?
Qwen3.5 9B is the better all-round choice, scoring 72/100 against GPT OSS 20B (64) and Qwen3 235B-A22B Instruct 2507 (58). It leads on price and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, GPT OSS 20B, Qwen3 235B-A22B Instruct 2507 or Qwen3.5 9B?
Qwen3.5 9B is cheaper at $0.10 input / $0.15 output per million tokens (median across 14 API providers). GPT OSS 20B costs $0.07 input / $0.295 output per million tokens (median across 18 API providers); Qwen3 235B-A22B Instruct 2507 costs $0.15 input / $0.75 output per million tokens (median across 11 API providers). At a typical mix of three input tokens to one output token, that is $0.113 per million tokens for Qwen3.5 9B versus $0.126 for GPT OSS 20B (1.1× as much) and $0.30 for Qwen3 235B-A22B Instruct 2507 (2.7× as much).
Which scores higher on benchmarks?
Qwen3.5 9B scores higher on the Capabilities Index (ECI): Qwen3.5 9B 139.5 (#101 of 148), Qwen3 235B-A22B Instruct 2507 138.9 (#105 of 148) and GPT OSS 20B 137.8 (#108 of 148). The confidence ranges of the top two overlap (136.5–141.3 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 GPT OSS 20B, Qwen3 235B-A22B Instruct 2507 and Qwen3.5 9B yet, so there is no like-for-like coding score. On overall capability, Qwen3.5 9B 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 Qwen3.5 9B have the largest context windows (262,144 and 262,144 tokens), against 131,072 for GPT OSS 20B. Maximum output per response: GPT OSS 20B up to 32,768, Qwen3 235B-A22B Instruct 2507 up to 16,384, Qwen3.5 9B up to 65,536 tokens.
Which can read images, PDFs, audio or video?
GPT OSS 20B accepts text; Qwen3 235B-A22B Instruct 2507 accepts text; Qwen3.5 9B accepts text, images and video. Qwen3.5 9B 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?
Qwen3.5 9B is the newest, released Feb 23, 2026. GPT OSS 20B came out Aug 5, 2025; Qwen3 235B-A22B Instruct 2507 came out Jul 21, 2025.
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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