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Deepseek vs Mistral Large
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 Large
Context window
32K
32,000 tokens · ~24K 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.
Deepseek has about 4× the context window of the other in this pair.
Deepseek has 300% more context capacity (128K vs 32K tokens). Deepseek is 90% cheaper on input.
Quick verdicts
Short takeaways — validate with your own workloads.
Long document processing
Use Deepseek. Its 128K context fits entire documents without chunking (vs 32K).
RAG / high-volume retrieval
Use Deepseek. Input tokens are 90% cheaper — critical when sending large retrieved contexts.
Long output (reports, code files)
Use Deepseek. Its 8K 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 | Deepseek | Mistral Large |
|---|---|---|
| Context window | 128,000 tokens (128K) | 32,000 tokens (32K) |
| Max output tokens | 8,192 tokens (8K) | 8,191 tokens (8K) |
| Speed tier | Balanced | Deep |
| Vision | No | No |
| Function calling | No | Yes |
| Extended thinking | Yes | No |
| Prompt caching | Yes | Yes |
| Batch API | No | No |
| Release date | N/A | Feb 2024 |
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 | Deepseek in | Deepseek out | Mistral Large in | Mistral Large out |
|---|---|---|---|---|
| Aws Bedrock | $0.580/M | $1.68/M | — | — |
| Azure | $1.14/M | $4.56/M | $4.00/M | $12.00/M |
| Deepinfra | $0.380/M | $0.890/M | — | — |
| Deepseek | $0.280/M | $0.420/M | — | — |
| Fireworks | $0.900/M | $0.900/M | — | — |
| Hyperbolic | $0.200/M | $0.200/M | — | — |
| Ibm Watsonx | — | — | $3.00/M | $10.00/M |
| Nebius | $0.500/M | $1.50/M | — | — |
| Novita | $0.400/M | $1.30/M | — | — |
| Openrouter | $0.140/M | $0.280/M | $8.00/M | $24.00/M |
| Replicate | $1.45/M | $1.45/M | — | — |
| Snowflake | — | — | — | — |
| Together Ai | $1.25/M | $1.25/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