Qwen3 30B A3B vs Ministral 14B
Ministral 14B comes out ahead, 63 to 55 on our weighted score, and it is the cheaper option too.
Alibaba (Qwen)Qwen3 30B A3B
55/100- ECI136.2
- Price$0.108 / $0.475
- Context131K
- Our pick
Mistral AIMinistral 14B
63/100- ECI—
- Price$0.175 / $0.175
- Context262K
Add a model
Make it a three-way comparison.
Ministral 14B is our pick
Ministral 14B is the better all-round choice, scoring 63/100 against Qwen3 30B A3B (55). It leads on price, 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 priceMinistral 14BMinistral 14B $0.175 · Qwen3 30B A3B $0.20 per 1M tokens (3:1 blend)
- Longest contextMinistral 14BMinistral 14B 262,144 · Qwen3 30B A3B 131,072 tokens
- Widest inputsMinistral 14BQwen3 30B A3B: Text · Ministral 14B: Text, Images
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Qwen3 30B A3B | Ministral 14B |
|---|---|---|---|
| Price | 50% | 80 | 82 |
| Inputs & features | 30% | 35 | 50 |
| Context window | 20% | 25 | 37 |
| Overall | 100% | 55/100 | 63/100 |
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 | Qwen3 30B A3BAlibaba (Qwen) | Ministral 14BMistral AI |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 136.2 | — |
| ECI rank | #126 of 165 | — |
| GPQA DiamondGraduate-level science questions | 61.7% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 62.8% | — |
| Price per million tokens | ||
| Input | $0.108 (best) | $0.175 |
| Output | $0.475 | $0.175 (best) |
| Cached input | — | — |
| Blended (3:1) | $0.20 | $0.175 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 14 providers | Median of 2 providers |
| Limits | ||
| Context window | 131,072 tokens | 262,144 tokens (best) |
| Max output | 16,384 tokens | 262,144 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | Yes |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yes | No |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Open | OpenApache-2.0 |
| API model ID | — | — |
| API providers | 14 (best) | 2 |
| Released | Apr 28, 2025 | Dec 2, 2025 |
| 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.
- Qwen3 30B A3B$2.03
- Ministral 14B$2.10
Which should you choose?
Which is better: Qwen3 30B A3B or Ministral 14B?
Ministral 14B is the better all-round choice, scoring 63/100 against Qwen3 30B A3B (55). It leads on price, 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, Qwen3 30B A3B or Ministral 14B?
Ministral 14B is cheaper at $0.175 input / $0.175 output per million tokens (median across 2 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 $0.175 per million tokens for Ministral 14B versus $0.20 for Qwen3 30B A3B (1.1× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Qwen3 30B A3B has an ECI of 136.2 and Ministral 14B has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3 30B A3B and Ministral 14B yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.
Which has the bigger context window?
Ministral 14B has the largest context window at 262,144 tokens, against 131,072 for Qwen3 30B A3B. Maximum output per response: Qwen3 30B A3B up to 16,384, Ministral 14B up to 262,144 tokens.
Which can read images, PDFs, audio or video?
Qwen3 30B A3B accepts text; Ministral 14B accepts text and images. Ministral 14B handles the widest range of inputs.
Are any of these open source?
Yes, both publish their weights (Apache-2.0), so you can self-host them.
Which is newer?
Ministral 14B is the newest, released Dec 2, 2025. Qwen3 30B A3B came out Apr 28, 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 Nov 2, 2026.
Related comparisons
- Add Gemini 2.5 Flash-Lite Preview 06-17Three-way comparison
- Qwen3 30B A3B vs Gemini 2.5 Flash-Lite Preview 06-17Google · ECI 133.8
- Qwen3 30B A3B vs DeepSeek V3 0324DeepSeek · ECI 135.9
- Qwen3 30B A3B vs GPT OSS 20BOpenAI · ECI 137.8
- Qwen3 30B A3B vs Llama 4 Maverick 17B InstructMeta · ECI 132.3
- Ministral 14B vs Rnj-1 InstructEssential AI
- Ministral 14B vs MiMo-V2-FlashXiaomi
