Compare
Deep Research Pro Preview 12 2025 vs Devstral 2 2512
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
Deep Research Pro Preview 12 2025
Context window
1.0M
1,048,576 tokens · ~786K 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.
Deep Research Pro Preview 12 2025 has about 4.1× the context window of the other in this pair.
Deep Research Pro Preview 12 2025 has 309% more context capacity (1048K vs 256K tokens). Devstral 2 2512 is 80% cheaper on input.
Quick verdicts
Short takeaways — validate with your own workloads.
Long document processing
Use Deep Research Pro Preview 12 2025. Its 1048K context fits entire documents without chunking (vs 256K).
RAG / high-volume retrieval
Use Devstral 2 2512. Input tokens are 80% cheaper — critical when sending large retrieved contexts.
Long output (reports, code files)
Use Devstral 2 2512. Its 256K 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 | Deep Research Pro Preview 12 2025 | Devstral 2 2512 |
|---|---|---|
| Context window | 1,048,576 tokens (1048K) | 256,000 tokens (256K) |
| Max output tokens | 65,536 tokens (65K) | 256,000 tokens (256K) |
| Speed tier | Balanced | Balanced |
| Vision | Yes | No |
| Function calling | No | Yes |
| Extended thinking | No | No |
| Prompt caching | No | Yes |
| Batch API | No | No |
| Release date | N/A | Dec 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 | Deep Research Pro Preview 12 2025 in | Deep Research Pro Preview 12 2025 out | Devstral 2 2512 in | Devstral 2 2512 out |
|---|---|---|---|---|
| $2.00/M | $12.00/M | — | — | |
| Mistral | — | — | $0.400/M | $2.00/M |
| Openrouter | — | — | $0.400/M | $2.00/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