Neither wins outright: Mistral: Codestral 2508 (batch) is the pick when cost matters at scale, Qwen: Qwen3 VL 8B Instruct when you need image input.
| Spec | Mistral: Codestral 2508 (batch) | Qwen: Qwen3 VL 8B Instruct |
|---|---|---|
| Provider | Mistral AI | Qwen |
| Input price (per 1M tokens) | $0.15 | $0.25 |
| Output price (per 1M tokens) | $0.45 | $0.75 |
| Blended price (3:1 input/output) | $0.22 | $0.38 |
| Cheaper than … of all models we track | 68% | 59% |
| Context window | 256K tokens (~384 pages) | 262K tokens (~393 pages) |
| Larger context than … of all models | 45% | 48% |
| Max output per response | 205K tokens (~153,600 words) | 236K tokens (~176,900 words) |
| Input types | text, file | image, text |
| Output types | text | text |
| Free variant | No | No |
| Listed since | 2025-08-01 | 2025-10-14 |
Monthly cost at list price for five common workloads. Token counts per unit are stated so you can scale them to your own traffic. A workload that does not fit a model's context window is marked rather than priced.
| Workload (per month) | Mistral: Codestral 2508 (batch) | Qwen: Qwen3 VL 8B Instruct | Difference |
|---|---|---|---|
| Customer-support chatbot 50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens) | $20.25 | $33.75 | Mistral: Codestral 2508 (batch) saves $13.50 |
| RAG search over documents 20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens) | $22.50 | $37.50 | Mistral: Codestral 2508 (batch) saves $15.00 |
| Coding / tool-using agent 2,000 tasks — each a multi-step task with tool calls and file context (60,000 in / 6,000 out tokens) | $23.40 | $39.00 | Mistral: Codestral 2508 (batch) saves $15.60 |
| Batch summarisation 10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens) | $14.70 | $24.50 | Mistral: Codestral 2508 (batch) saves $9.80 |
| Long-document analysis 500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens) | $7.95 | $13.25 | Mistral: Codestral 2508 (batch) saves $5.30 |
| Capability | Mistral: Codestral 2508 (batch) | Qwen: Qwen3 VL 8B Instruct | What it lets you do |
|---|---|---|---|
| Tool / function calling | ✓ Yes | ✓ Yes | call your APIs and run agent loops |
| Structured output (JSON schema) | ✓ Yes | ✓ Yes | return JSON that validates against your schema |
| Reasoning / thinking mode | — | — | spend extra tokens thinking before answering hard problems |
| Image input | — | ✓ Yes | read screenshots, charts and scanned pages |
| Audio input | — | — | take speech or audio directly |
| File / PDF input | ✓ Yes | — | accept documents without your own parsing step |
| Image output | — | — | generate images, not just text |
| Built-in web search | — | — | answer from live web results |
| Seed (reproducible sampling) | ✓ Yes | ✓ Yes | repeat a generation for tests and evals |
| Log-probabilities | — | ✓ Yes | read token confidence for classification and scoring |
From each model's published parameters and input/output types. “—” means not advertised, not proven absent.
| Date | Model | Input / 1M | Output / 1M |
|---|---|---|---|
| 2026-10-10 | Qwen: Qwen3 VL 8B Instruct | $0.25 | $0.75 |
| 2026-09-10 | Mistral: Codestral 2508 (batch) | $0.15 | $0.45 |
| 2026-08-06 | Qwen: Qwen3 VL 8B Instruct | $0.12 | $0.46 |
Neither wins outright: Mistral: Codestral 2508 (batch) is the pick when cost matters at scale, Qwen: Qwen3 VL 8B Instruct when you need image input. In short: Mistral: Codestral 2508 (batch) when cost matters at scale, you need file / PDF input; Qwen: Qwen3 VL 8B Instruct when you need image input, you need log-probabilities.
Mistral: Codestral 2508 (batch) is cheaper: $0.22 vs $0.38 per 1M tokens at a typical 3:1 input/output mix, 40% less. For 50,000 support conversations a month that is $20.25 against $33.75.
Mistral: Codestral 2508 (batch) costs $0.15 per 1M input tokens and $0.45 per 1M output tokens; Qwen: Qwen3 VL 8B Instruct costs $0.25 input and $0.75 output. Output tokens are billed separately, so long answers shift the gap.
Qwen: Qwen3 VL 8B Instruct: 262K tokens, about 393 pages, against 256K (about 384 pages) for Mistral: Codestral 2508 (batch).
Tool calling — Mistral: Codestral 2508 (batch): yes, Qwen: Qwen3 VL 8B Instruct: yes. JSON-schema structured output — Mistral: Codestral 2508 (batch): yes, Qwen: Qwen3 VL 8B Instruct: yes.
Only Qwen: Qwen3 VL 8B Instruct accepts image input; Mistral: Codestral 2508 (batch) is text-only for input.
No free variant is listed for either; both are pay-per-token.
Mistral: Codestral 2508 (batch) can write up to 205K tokens (about 153,600 words) per response; Qwen: Qwen3 VL 8B Instruct up to 236K (about 176,900 words).
Mistral: Codestral 2508 (batch) was listed on 2025-08-01; Qwen: Qwen3 VL 8B Instruct on 2025-10-14.
Mistral: Codestral 2508 (batch): input price cut 50% ($0.30 → $0.15/1M), output price cut 50% ($0.90 → $0.45/1M) on 2026-09-10. Qwen: Qwen3 VL 8B Instruct: input price raised 53% ($0.12 → $0.25/1M), output price raised 39% ($0.46 → $0.75/1M) on 2026-10-10 (2 price changes since 2026-03-10).
Mistral's cutting-edge language model for coding released end of July 2025. Codestral specializes in low-latency, high-frequency tasks such as fill-in-the-middle (FIM), code correction and test generation. [Blog Post](https://mistral.ai/news/codestral-25-08)
Full Mistral: Codestral 2508 (batch) specs →Qwen3-VL-8B-Instruct is a multimodal vision-language model from the Qwen3-VL series, built for high-fidelity understanding and reasoning across text, images, and video. It features improved multimodal fusion with Interleaved-MRoPE for long-horizon...
Full Qwen: Qwen3 VL 8B Instruct specs →