Compare
Codestral 2508 vs DeepSeek V4 Flash (free)
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
DeepSeek V4 Flash (free)
Context window
256K
256,000 tokens · ~192K 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.
Same context window size for both models.
Codestral 2508 and DeepSeek V4 Flash (free) have identical context windows (256K tokens).
Full specs
Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.
| Spec | Codestral 2508 | DeepSeek V4 Flash (free) |
|---|---|---|
| Context window | 256,000 tokens (256K) | 256,000 tokens (256K) |
| Max output tokens | 256,000 tokens (256K) | 256,000 tokens (256K) |
| Speed tier | Balanced | Fast |
| Vision | No | No |
| Function calling | Yes | Yes |
| Extended thinking | No | Yes |
| Prompt caching | Yes | No |
| Batch API | No | No |
| Release date | Aug 2025 | Apr 2026 |
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 2508 in | Codestral 2508 out | DeepSeek V4 Flash (free) in | DeepSeek V4 Flash (free) out |
|---|---|---|---|---|
| Mistral | $0.300/M | $0.900/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