Qwen3.8 Max (0902) Open vs 
Mistral Large Paid
Qwen3.8 Max (0902) vs Mistral Large compared — price per token, context window, multimodality, openness and which to choose. Can the open-source model replace the paid one? Full 2026 breakdown.
Mistral Large — full profile ›
Prices & specs refreshed from live data · olud.ai
Open-model prices = cheapest provider via OpenRouter; official maker rates may be higher.
$6 /M outputNo per-token fees if you self-host
$6 /M outputManaged API (no infra to run)
Qwen3.8 Max (0902) vs Mistral Large specs
| Spec | Qwen3.8 Max (0902) | Mistral Large | Winner |
|---|---|---|---|
| Maker | Alibaba | Mistral AI | – |
| Type | Open-weight | Proprietary | |
| Context window | 1M tokens | 128K tokens | |
| Input price | $2/M · free self-host | $2/M | = Tie |
| Output price | $6/M · free self-host | $6/M | = Tie |
| Vision / multimodal | Yes | No | |
| Tool / function calling | Yes | Yes | = Tie |
| Self-hostable | Yes | No (API only) | |
| License | Apache 2.0 | Proprietary |
Price gap & when to choose each
- You want to self-host or run on your cloud
- You need the longer 1M context window
- You prioritize data privacy & control
- You want the lowest operating costs
- You are building open or reproducible AI
- You want frontier performance through a managed API
- You value reliability & ecosystem
- You don't want to manage infrastructure
Feature comparison
| Capability | Qwen3.8 Max (0902) | Mistral Large |
|---|---|---|
| Open weights (downloadable) | ✓ | ✗ |
| Self-hostable | ✓ | ✗ |
| Runs fully offline | ✓ | ✗ |
| Vision / multimodal | ✓ | ✗ |
| Tool / function calling | ✓ | ✓ |
| 1M+ context window | ✓ | ✗ |
Benchmarks: Qwen3.8 Max (0902) vs Mistral Large
Independent benchmark scores measured by Artificial Analysis. Higher is better (except latency).
Benchmark data by Artificial Analysis.
How Qwen3.8 Max (0902) and Mistral Large score
| Criterion | Qwen3.8 Max (0902) | Mistral Large |
|---|---|---|
| Cost-efficiency | 4.0 | 4.0 |
| Context window | 5.0 | 3.5 |
| Openness | 5.0 | 1.5 |
| Self-hosting | 5.0 | 1.0 |
| Multimodality | 5.0 | 3.5 |
Scores come from live data — output price (cost), context length, open vs closed weights (openness & self-hosting) and vision/tool support (multimodality). Raw task quality isn't scored here; it depends on your benchmark — see the verdict.
What each model is
Qwen3.8 Max (0902) Open
Qwen3.8 Max 0902 is an updated snapshot of Qwen3.8 Max from Alibaba's Qwen team. It is a 2.4-trillion-parameter mixture-of-experts model that accepts text, image, and video input and returns text,...
Mistral Large Paid
This is Mistral AI's flagship model, Mistral Large 2 (version `mistral-large-2407`). It's a proprietary weights-available model and excels at reasoning, code, JSON, chat, and more. Read the launch announcement [here](https://mistral.ai/news
Other models in these families
These variants are tracked but not compared here — one page per family keeps the comparison readable.
Frequently asked questions
Is Qwen3.8 Max (0902) as good as Mistral Large?
Qwen3.8 Max (0902) is open-weight and competitive on many tasks, but Mistral Large may still lead on the hardest reasoning and agentic work. The gap keeps narrowing — benchmark both on your actual use case before deciding.
Can I run Qwen3.8 Max (0902) locally?
Yes. Qwen3.8 Max (0902) has open weights, so you can self-host it on your own GPUs or run it via a low-cost API. Mistral Large is API-only and cannot be self-hosted.
Qwen3.8 Max (0902) vs Mistral Large — which should I pick in 2026?
Choose Qwen3.8 Max (0902) if you want to self-host, keep your data private and skip per-token fees — it's open-weight and runs on your own hardware. Choose Mistral Large if you want frontier capability through a managed API with zero infrastructure to run.
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