Compare
Mixtral 8x22B Instruct vs Qwen3 235B A22B Thinking 2507
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
Mixtral 8x22B Instruct
Context window
66K
65,536 tokens · ~49K words
Model
Qwen3 235B A22B Thinking 2507
Context window
262K
262,144 tokens · ~197K 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 235B A22B Thinking 2507 has about 4× the context window of the other in this pair.
Qwen3 235B A22B Thinking 2507 has 300% more context capacity (262K vs 65K tokens). Qwen3 235B A22B Thinking 2507 is 83% cheaper on input.
Quick verdicts
Short takeaways — validate with your own workloads.
Long document processing
Use Qwen3 235B A22B Thinking 2507. Its 262K context fits entire documents without chunking (vs 65K).
RAG / high-volume retrieval
Use Qwen3 235B A22B Thinking 2507. Input tokens are 83% cheaper — critical when sending large retrieved contexts.
Full specs
Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.
| Spec | Mixtral 8x22B Instruct | Qwen3 235B A22B Thinking 2507 |
|---|---|---|
| Context window | 65,536 tokens (65K) | 262,144 tokens (262K) |
| Max output tokens | N/A | 262,144 tokens (262K) |
| Speed tier | Balanced | Deep |
| Vision | No | No |
| Function calling | Yes | Yes |
| Extended thinking | No | Yes |
| Prompt caching | Yes | Yes |
| Batch API | No | No |
| Release date | Apr 2024 | Jul 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 | Mixtral 8x22B Instruct in | Mixtral 8x22B Instruct out | Qwen3 235B A22B Thinking 2507 in | Qwen3 235B A22B Thinking 2507 out |
|---|---|---|---|---|
| Deepinfra | — | — | $0.300/M | $2.90/M |
| Fireworks | $1.20/M | $1.20/M | $0.220/M | $0.880/M |
| Novita | — | — | $0.300/M | $3.00/M |
| Openrouter | $0.650/M | $0.650/M | $0.110/M | $0.600/M |
| Together Ai | — | — | $0.650/M | $3.00/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