Side-by-side comparison
Codestral 2508 vs Qwen3.5-35B-A3B
Qwen
Qwen3.5-35B-A3B
👁 Vision
🔧 Tools
{} JSON
Input / 1M
$0.1400
Output / 1M
$1.0000
| Codestral 2508 | Qwen3.5-35B-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 | 0.1400 |
| 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 Qwen3.5-35B-A3B?
Qwen3.5-35B-A3B is cheaper than Codestral 2508 on a 50/50 input/output blend by about $0.03 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 Qwen3.5-35B-A3B?
Qwen3.5-35B-A3B has the larger context window at 262k tokens versus 256k tokens for Codestral 2508. That means Qwen3.5-35B-A3B can ingest about 1.0x as much text per request.
What is the difference between Codestral 2508 and Qwen3.5-35B-A3B?
Codestral 2508 comes from Mistral; Qwen3.5-35B-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.