Qwen3.5 35B-A3B Base vs Qwen3.5 9B Base vs Mistral Large 3
Too close to call on our weighted score (Mistral Large 3 52, Qwen3.5 9B Base 50, Qwen3.5 35B-A3B Base 45). The right pick depends on what you value most.
Alibaba (Qwen)Qwen3.5 35B-A3B Base
45/100- ECI—
- Price$0.54 / $1.33
- Context262K
- Alibaba (Qwen)
Qwen3.5 9B Base
50/100- ECI—
- Price$0.30 / $0.807
- Context262K
Mistral AIMistral Large 3
52/100- ECI—
- Price$0.50 / $1.50
- Context262K
Too close to call
It is close. Our weighted score puts them within 2 points (Mistral Large 3 52/100, Qwen3.5 9B Base 50/100, Qwen3.5 35B-A3B Base 45/100), so choose by what matters most for your work: Qwen3.5 9B Base on price. 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 priceQwen3.5 9B BaseQwen3.5 9B Base $0.427 · Qwen3.5 35B-A3B Base $0.739 · Mistral Large 3 $0.75 per 1M tokens (3:1 blend)
- Longest contextAbout the sameQwen3.5 35B-A3B Base 262,144 · Qwen3.5 9B Base 262,144 · Mistral Large 3 262,144 tokens
- Widest inputsQwen3.5 35B-A3B Base and Qwen3.5 9B BaseQwen3.5 35B-A3B Base: Text, Images, Video · Qwen3.5 9B Base: Text, Images, Video · Mistral Large 3: Text, Images
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Qwen3.5 35B-A3B Base | Qwen3.5 9B Base | Mistral Large 3 |
|---|---|---|---|---|
| Price | 50% | 54 | 65 | 53 |
| Inputs & features | 30% | 35 | 35 | 60 |
| Context window | 20% | 37 | 37 | 37 |
| Overall | 100% | 45/100 | 50/100 | 52/100 |
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 | Qwen3.5 35B-A3B BaseAlibaba (Qwen) | Qwen3.5 9B BaseAlibaba (Qwen) | Mistral Large 3Mistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.54 | $0.30 (best) | $0.50 |
| Output | $1.33 | $0.807 (best) | $1.50 |
| Cached input | — | — | $0.05 |
| Blended (3:1) | $0.739 | $0.427 (best) | $0.75 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 1 providers | Median of 1 providers | Official Mistral API |
| Limits | |||
| Context window | 262,144 tokens | 262,144 tokens | 262,144 tokens |
| Max output | 65,536 tokens | 65,536 tokens | 262,144 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | Yes | Yes | No |
| Reasoning | No | No | No |
| Tool calling | No | No | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | OpenApache-2.0 | OpenApache-2.0 | Open |
| API model ID | — | — | mistral-large-2512 |
| API providers | 1 | 1 | 17 (best) |
| Released | Feb 24, 2026 | Feb 26, 2026 | Dec 2, 2025 |
| Knowledge cutoff | — | — | Nov 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Qwen3.5 35B-A3B Base$8.07
- Qwen3.5 9B Base$4.61
- Mistral Large 3$8.00
Which should you choose?
Which is better: Qwen3.5 35B-A3B Base, Qwen3.5 9B Base or Mistral Large 3?
It is close. Our weighted score puts them within 2 points (Mistral Large 3 52/100, Qwen3.5 9B Base 50/100, Qwen3.5 35B-A3B Base 45/100), so choose by what matters most for your work: Qwen3.5 9B Base on price. 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, Qwen3.5 35B-A3B Base, Qwen3.5 9B Base or Mistral Large 3?
Qwen3.5 9B Base is cheaper at $0.30 input / $0.807 output per million tokens (median across 1 API provider). Qwen3.5 35B-A3B Base costs $0.54 input / $1.33 output per million tokens (median across 1 API provider); Mistral Large 3 costs $0.50 input / $1.50 output per million tokens (official Mistral API price). At a typical mix of three input tokens to one output token, that is $0.427 per million tokens for Qwen3.5 9B Base versus $0.739 for Qwen3.5 35B-A3B Base (1.7× as much) and $0.75 for Mistral Large 3 (1.8× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Qwen3.5 35B-A3B Base has not been scored yet, Qwen3.5 9B Base has not been scored yet and Mistral Large 3 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3.5 35B-A3B Base, Qwen3.5 9B Base and Mistral Large 3 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Qwen3.5 35B-A3B Base and Qwen3.5 9B Base does not support tool calling, which most coding agents need.
Which has the bigger context window?
Qwen3.5 35B-A3B Base, Qwen3.5 9B Base and Mistral Large 3 share the same 262,144-token context window. Maximum output per response: Qwen3.5 35B-A3B Base up to 65,536, Qwen3.5 9B Base up to 65,536, Mistral Large 3 up to 262,144 tokens.
Which can read images, PDFs, audio or video?
Qwen3.5 35B-A3B Base accepts text, images and video; Qwen3.5 9B Base accepts text, images and video; Mistral Large 3 accepts text and images. Qwen3.5 35B-A3B Base 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 Base is the newest, released Feb 26, 2026. Qwen3.5 35B-A3B Base came out Feb 24, 2026; Mistral Large 3 came out Dec 2, 2025. Knowledge cutoff: Mistral Large 3 Nov 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.
