Compare
Codestral 2 001 vs Deepseek
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.
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.
Same context window size for both models.
Codestral 2 001 and Deepseek have identical context windows (128K tokens). Deepseek is 6% cheaper on input.
Quick verdicts
Short takeaways — validate with your own workloads.
RAG / high-volume retrieval
Use Deepseek. Input tokens are 6% cheaper — critical when sending large retrieved contexts.
Long output (reports, code files)
Use Codestral 2 001. Its 128K 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 | Codestral 2 001 | Deepseek |
|---|---|---|
| Context window | 128,000 tokens (128K) | 128,000 tokens (128K) |
| Max output tokens | 128,000 tokens (128K) | 8,192 tokens (8K) |
| Speed tier | Balanced | Balanced |
| Vision | No | No |
| Function calling | Yes | No |
| Extended thinking | No | Yes |
| Prompt caching | No | Yes |
| Batch API | No | No |
| Release date | N/A | N/A |
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 | Codestral 2 001 in | Codestral 2 001 out | Deepseek in | Deepseek out |
|---|---|---|---|---|
| Aws Bedrock | — | — | $0.580/M | $1.68/M |
| Azure | — | — | $1.14/M | $4.56/M |
| Deepinfra | — | — | $0.380/M | $0.890/M |
| Deepseek | — | — | $0.280/M | $0.420/M |
| Fireworks | — | — | $0.900/M | $0.900/M |
| Google Vertex | $0.300/M | $0.900/M | — | — |
| Hyperbolic | — | — | $0.200/M | $0.200/M |
| Nebius | — | — | $0.500/M | $1.50/M |
| Novita | — | — | $0.400/M | $1.30/M |
| Openrouter | — | — | $0.140/M | $0.280/M |
| Replicate | — | — | $1.45/M | $1.45/M |
| 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