QwQ 32B vs Qwen3-Next 80B-A3B Instruct vs GPT-4.1 mini
GPT-4.1 mini comes out ahead, 62 to 43 and 39 on our weighted score, and it is the cheaper option too.
Alibaba (Qwen)QwQ 32B
43/100- ECI137.6
- Price$0.66 / $1.00
- Context131K
- Alibaba (Qwen)
Qwen3-Next 80B-A3B Instruct
39/100- ECI—
- Price$0.50 / $2.00
- Context131K
- Our pick
OpenAIGPT-4.1 mini
62/100- ECI135.0
- Price$0.40 / $1.60
- Context1.05M
GPT-4.1 mini is our pick
GPT-4.1 mini is the better all-round choice, scoring 62/100 against QwQ 32B (43) and Qwen3-Next 80B-A3B Instruct (39). It leads on inputs & features and context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceGPT-4.1 miniGPT-4.1 mini $0.70 · QwQ 32B $0.745 · Qwen3-Next 80B-A3B Instruct $0.875 per 1M tokens (3:1 blend)
- Longest contextGPT-4.1 miniGPT-4.1 mini 1,047,576 · QwQ 32B 131,072 · Qwen3-Next 80B-A3B Instruct 131,072 tokens
- Widest inputsGPT-4.1 miniQwQ 32B: Text · Qwen3-Next 80B-A3B Instruct: Text · GPT-4.1 mini: Text, Images, PDFs
- Self-hostingQwQ 32B and Qwen3-Next 80B-A3B InstructPublishes downloadable weights
| Measure | Weight | QwQ 32B | Qwen3-Next 80B-A3B Instruct | GPT-4.1 mini |
|---|---|---|---|---|
| Price | 50% | 56 | 53 | 57 |
| Inputs & features | 30% | 35 | 25 | 70 |
| Context window | 20% | 24 | 24 | 61 |
| Overall | 100% | 43/100 | 39/100 | 62/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | QwQ 32BAlibaba (Qwen) | Qwen3-Next 80B-A3B InstructAlibaba (Qwen) | GPT-4.1 miniOpenAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 137.6 (best) | — | 135.0 |
| ECI rank | #109 of 148 (best) | — | #115 of 148 |
| GPQA DiamondGraduate-level science questions | 65.3% | — | 65.9% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | — | — | 6.7% |
| OTIS Mock AIME 2024–2025Competition mathematics | 59.2% (best) | — | 44.7% |
| SimpleQA VerifiedShort factual questions | — | — | 12.7% |
| Price per million tokens | |||
| Input | $0.66 | $0.50 | $0.40 (best) |
| Output | $1.00 (best) | $2.00 | $1.60 |
| Cached input | — | — | $0.10 |
| Blended (3:1) | $0.745 | $0.875 | $0.70 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 1 providers | Official Alibaba API | Official OpenAI API |
| Limits | |||
| Context window | 131,072 tokens | 131,072 tokens | 1,047,576 tokens (best) |
| Max output | 8,192 tokens | 32,768 tokens (best) | 32,768 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | Yes |
| PDFs | No | No | Yes |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | — | qwen3-next-80b-a3b-instruct | gpt-4.1-mini |
| API providers | 1 | 13 | 24 (best) |
| Released | Mar 5, 2025 | Sep 2025 | Apr 14, 2025 |
| Knowledge cutoff | Apr 2024 | Apr 2025 | Apr 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- QwQ 32B$8.60
- Qwen3-Next 80B-A3B Instruct$9.00
- GPT-4.1 mini$7.20
Which should you choose?
Which is better: QwQ 32B, Qwen3-Next 80B-A3B Instruct or GPT-4.1 mini?
GPT-4.1 mini is the better all-round choice, scoring 62/100 against QwQ 32B (43) and Qwen3-Next 80B-A3B Instruct (39). It leads on inputs & features and context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, QwQ 32B, Qwen3-Next 80B-A3B Instruct or GPT-4.1 mini?
GPT-4.1 mini is cheaper at $0.40 input / $1.60 output per million tokens (official OpenAI API price). QwQ 32B costs $0.66 input / $1.00 output per million tokens (median across 1 API provider); Qwen3-Next 80B-A3B Instruct costs $0.50 input / $2.00 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.70 per million tokens for GPT-4.1 mini versus $0.745 for QwQ 32B (1.1× as much) and $0.875 for Qwen3-Next 80B-A3B Instruct (1.3× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. QwQ 32B has an ECI of 137.6, Qwen3-Next 80B-A3B Instruct has not been scored yet and GPT-4.1 mini has an ECI of 135.0.
Which is better for coding?
There are no published SWE-bench Verified results for QwQ 32B, Qwen3-Next 80B-A3B Instruct and GPT-4.1 mini yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
GPT-4.1 mini has the largest context window at 1,047,576 tokens, against 131,072 for QwQ 32B and 131,072 for Qwen3-Next 80B-A3B Instruct. Maximum output per response: QwQ 32B up to 8,192, Qwen3-Next 80B-A3B Instruct up to 32,768, GPT-4.1 mini up to 32,768 tokens.
Which can read images, PDFs, audio or video?
QwQ 32B accepts text; Qwen3-Next 80B-A3B Instruct accepts text; GPT-4.1 mini accepts text, images and PDFs. GPT-4.1 mini handles the widest range of inputs.
Are any of these open source?
QwQ 32B and Qwen3-Next 80B-A3B Instruct publishes its weights and can be self-hosted; GPT-4.1 mini is proprietary.
Which is newer?
Qwen3-Next 80B-A3B Instruct is the newest, released Sep 2025. GPT-4.1 mini came out Apr 14, 2025; QwQ 32B came out Mar 5, 2025. Knowledge cutoff: QwQ 32B Apr 2024, Qwen3-Next 80B-A3B Instruct Apr 2025, GPT-4.1 mini Apr 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.
