Qwen3 30B-A3B Instruct 2507 vs Qwen3 30B A3B vs GPT OSS 20B
Too close to call on our weighted score (GPT OSS 20B 61, Qwen3 30B-A3B Instruct 2507 59, Qwen3 30B A3B 57). The right pick depends on what you value most.
Alibaba (Qwen)
Qwen3 30B-A3B Instruct 2507
59/100- ECI137.3
- Price$0.10 / $0.30
- Context262K
Alibaba (Qwen)
Qwen3 30B A3B
57/100- ECI136.2
- Price$0.108 / $0.475
- Context131K
OpenAI
GPT OSS 20B
61/100- ECI137.8
- Price$0.07 / $0.25
- Context131K
Too close to call
It is close. Our weighted score puts them within 2 points (GPT OSS 20B 61/100, Qwen3 30B-A3B Instruct 2507 59/100, Qwen3 30B A3B 57/100), so choose by what matters most for your work: GPT OSS 20B for raw capability and Qwen3 30B-A3B Instruct 2507 for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGPT OSS 20BCapabilities Index (ECI): GPT OSS 20B 137.8 · Qwen3 30B-A3B Instruct 2507 137.3 · Qwen3 30B A3B 136.2
- Lowest priceGPT OSS 20BGPT OSS 20B $0.115 · Qwen3 30B-A3B Instruct 2507 $0.15 · Qwen3 30B A3B $0.20 per 1M tokens (3:1 blend)
- Longest contextQwen3 30B-A3B Instruct 2507Qwen3 30B-A3B Instruct 2507 262,144 · Qwen3 30B A3B 131,072 · GPT OSS 20B 131,072 tokens
- Widest inputsSame inputsQwen3 30B-A3B Instruct 2507: Text · Qwen3 30B A3B: Text · GPT OSS 20B: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Qwen3 30B-A3B Instruct 2507 | Qwen3 30B A3B | GPT OSS 20B |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 61 | 59 | 61 |
| Price | 25% | 85 | 80 | 90 |
| Inputs & features | 15% | 25 | 35 | 35 |
| Context window | 10% | 37 | 25 | 25 |
| Overall | 100% | 59/100 | 57/100 | 61/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 137.3 | 136.2 | 137.8 (best) |
| ECI rank | #124 of 165 | #126 of 165 | #122 of 165 (best) |
| GPQA DiamondGraduate-level science questions | 55.6% | 61.7% (best) | 60.8% |
| OTIS Mock AIME 2024–2025Competition mathematics | 62.2% | 62.8% | 65.3% (best) |
| Price per million tokens | |||
| Input | $0.10 | $0.108 | $0.07 (best) |
| Output | $0.30 | $0.475 | $0.25 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.15 | $0.20 | $0.115 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 12 providers | Median of 14 providers | Median of 37 providers |
| Limits | |||
| Context window | 262,144 tokens (best) | 131,072 tokens | 131,072 tokens |
| Max output | 16,384 tokens | 16,384 tokens | 32,768 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | 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 | No | No |
| Availability | |||
| Weights | OpenApache 2.0 | Open | Open |
| API model ID | — | — | — |
| API providers | 14 | 14 | 41 (best) |
| Released | Jul 28, 2025 | Apr 28, 2025 | 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 30B-A3B Instruct 2507$1.60
Qwen3 30B A3B$2.03
GPT OSS 20B$1.20
Which should you choose?
Which is better: Qwen3 30B-A3B Instruct 2507, Qwen3 30B A3B or GPT OSS 20B?
It is close. Our weighted score puts them within 2 points (GPT OSS 20B 61/100, Qwen3 30B-A3B Instruct 2507 59/100, Qwen3 30B A3B 57/100), so choose by what matters most for your work: GPT OSS 20B for raw capability and Qwen3 30B-A3B Instruct 2507 for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Qwen3 30B-A3B Instruct 2507, Qwen3 30B A3B or GPT OSS 20B?
GPT OSS 20B is cheaper at $0.07 input / $0.25 output per million tokens (median across 37 API providers). Qwen3 30B-A3B Instruct 2507 costs $0.10 input / $0.30 output per million tokens (median across 12 API providers); Qwen3 30B A3B costs $0.108 input / $0.475 output per million tokens (median across 14 API providers). At a typical mix of three input tokens to one output token, that is $0.115 per million tokens for GPT OSS 20B versus $0.15 for Qwen3 30B-A3B Instruct 2507 (1.3× as much) and $0.20 for Qwen3 30B A3B (1.7× as much).
Which scores higher on benchmarks?
GPT OSS 20B scores higher on the Capabilities Index (ECI): GPT OSS 20B 137.8 (#122 of 165), Qwen3 30B-A3B Instruct 2507 137.3 (#124 of 165) and Qwen3 30B A3B 136.2 (#126 of 165). The confidence ranges of the top two overlap (133.1–139.7 vs 131.7–139.4), so treat the gap as small. On individual benchmarks: GPQA Diamond — Qwen3 30B A3B 61.7%, GPT OSS 20B 60.8%, Qwen3 30B-A3B Instruct 2507 55.6%; OTIS Mock AIME 2024–2025 — GPT OSS 20B 65.3%, Qwen3 30B A3B 62.8%, Qwen3 30B-A3B Instruct 2507 62.2%.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3 30B-A3B Instruct 2507, Qwen3 30B A3B and GPT OSS 20B yet, so there is no like-for-like coding score. On overall capability, GPT OSS 20B 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 30B-A3B Instruct 2507 has the largest context window at 262,144 tokens, against 131,072 for Qwen3 30B A3B and 131,072 for GPT OSS 20B. Maximum output per response: Qwen3 30B-A3B Instruct 2507 up to 16,384, Qwen3 30B A3B up to 16,384, GPT OSS 20B up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Qwen3 30B-A3B Instruct 2507 accepts text; Qwen3 30B A3B accepts text; GPT OSS 20B accepts text. They handle the same number of input types.
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 20B is the newest, released Aug 5, 2025. Qwen3 30B-A3B Instruct 2507 came out Jul 28, 2025; Qwen3 30B A3B came out Apr 28, 2025. Knowledge cutoff: GPT OSS 20B 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.