Compare
Mistral Mixtral 8x7b Instruct vs Qwen3 VL 235B A22B Thinking
This page is context-first: how much text each model can take in one request. Full specs adds capabilities and limits; the pricing matrix below is only about $/million tokens from hosts that list both models.
Model
Mistral Mixtral 8x7b Instruct
Context window
32K
32,000 tokens · ~24K words
Model
Qwen3 VL 235B A22B Thinking
Context window
131K
131,072 tokens · ~98K words
Context window · side by side
Bar length is relative to the larger of the two windows (100% = max of this pair). This is not pricing.
Qwen3 VL 235B A22B Thinking has about 4.1× the context window of the other in this pair.
Qwen3 VL 235B A22B Thinking has 309% more context capacity (131K vs 32K tokens). Qwen3 VL 235B A22B Thinking is 62% cheaper on input.
Quick verdicts
Short takeaways — validate with your own workloads.
Long document processing
Use Qwen3 VL 235B A22B Thinking. Its 131K context fits entire documents without chunking (vs 32K).
RAG / high-volume retrieval
Use Qwen3 VL 235B A22B Thinking. Input tokens are 62% cheaper — critical when sending large retrieved contexts.
Long output (reports, code files)
Use Qwen3 VL 235B A22B Thinking. Its 32K max output lets you generate complete artifacts in one request.
Full specs
Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.
| Spec | Mistral Mixtral 8x7b Instruct | Qwen3 VL 235B A22B Thinking |
|---|---|---|
| Context window | 32,000 tokens (32K) | 131,072 tokens (131K) |
| Max output tokens | 8,191 tokens (8K) | 32,768 tokens (32K) |
| Speed tier | Fast | Deep |
| Vision | No | Yes |
| Function calling | No | Yes |
| Extended thinking | No | Yes |
| Prompt caching | No | No |
| Batch API | No | No |
| Release date | N/A | Sep 2025 |
Pricing matrix
Dollar rates only: hosts that list both models, per 1M tokens. For how much text fits, use the context section above — not this table.
| Provider | Mistral Mixtral 8x7b Instruct in | Mistral Mixtral 8x7b Instruct out | Qwen3 VL 235B A22B Thinking in | Qwen3 VL 235B A22B Thinking out |
|---|---|---|---|---|
| Alibaba Cloud | — | — | $0.400/M | $4.00/M |
| Aws Bedrock | $0.590/M | $0.910/M | — | — |
| Fireworks | — | — | $0.220/M | $0.880/M |
| Novita | — | — | $0.980/M | $3.95/M |
Frequently asked questions
Powered by Mem0
Use a smaller model.
Get better results.
Mem0 gives your AI long-term memory so you stop re-sending context on every call. That means you can use a smaller, faster, cheaper model — and still get better answers.
Example: a multi-turn chat session
80% less to send — works with any model