Side-by-side comparison
Codestral 2508 vs Qwen3.6 35B A3B
Qwen
Qwen3.6 35B A3B
👁 Vision
🔧 Tools
{} JSON
Input / 1M
$0.1500
Output / 1M
$1.0000
| Codestral 2508 | Qwen3.6 35B A3B | |
|---|---|---|
| Provider | Mistral | Qwen |
| Context window Maximum tokens (input + output) the model can process in a single request. Glossary → | 256,000 | 262,144 |
| Capabilities Optional capabilities the model advertises: vision (images), tools (function calling), json_mode (structured output). | tools, json_mode | vision, tools, json_mode |
| Input $ / 1M tokens Cost for tokens you send (prompt + context). Cheaper side highlighted. Glossary → | 0.3000 | 0.1500 |
| Output $ / 1M tokens Cost for tokens the model generates. Output is normally 3–5× pricier than input. Glossary → | 0.9000 | 1.0000 |
Frequently asked questions
Which is cheaper, Codestral 2508 or Qwen3.6 35B A3B?
Qwen3.6 35B A3B is cheaper than Codestral 2508 on a 50/50 input/output blend by about $0.025 per 1M tokens. Exact savings depend on your input-vs-output ratio — use the cost calculator on this page for a workload-specific estimate.
Which has a larger context window, Codestral 2508 or Qwen3.6 35B A3B?
Qwen3.6 35B A3B has the larger context window at 262k tokens versus 256k tokens for Codestral 2508. That means Qwen3.6 35B A3B can ingest about 1.0x as much text per request.
What is the difference between Codestral 2508 and Qwen3.6 35B A3B?
Codestral 2508 comes from Mistral; Qwen3.6 35B A3B comes from Qwen. They differ in pricing, context window, and supported capabilities — see the side-by-side table on this page for the exact figures, refreshed nightly.