Mistral: Mistral Medium 3.1 (batch) vs Qwen: Qwen3 VL 32B Instruct
Neither wins outright: Mistral: Mistral Medium 3.1 (batch) is the pick when you need file / PDF input, Qwen: Qwen3 VL 32B Instruct when cost matters at scale.
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: Mistral Medium 3.1 (batch)
Qwen: Qwen3 VL 32B Instruct
Difference
Customer-support chatbot
50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens)
$35.00
$16.12
Qwen: Qwen3 VL 32B Instruct saves $18.88
RAG search over documents
20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens)
$34.00
$16.64
Qwen: Qwen3 VL 32B Instruct saves $17.36
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)
$36.00
$17.47
Qwen: Qwen3 VL 32B Instruct saves $18.53
Batch summarisation
10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens)
$22.00
$10.82
Qwen: Qwen3 VL 32B Instruct saves $11.18
Long-document analysis
500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens)
$11.00
$5.62
Qwen: Qwen3 VL 32B Instruct saves $5.38
Capabilities side by side
Capability
Mistral: Mistral Medium 3.1 (batch)
Qwen: Qwen3 VL 32B 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
✓ 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.
Qwen: Qwen3 VL 32B Instruct: price unchanged since we started tracking it on 2026-03-10.
Date
Model
Input / 1M
Output / 1M
2026-09-10
Mistral: Mistral Medium 3.1 (batch)
$0.20
$1.00
Which should you choose?
Choose Mistral: Mistral Medium 3.1 (batch) if…
you need file / PDF input — to accept documents without your own parsing step; Qwen: Qwen3 VL 32B Instruct does not advertise it
you generate long outputs in one go — up to 105K tokens (about 78,600 words) per response
Choose Qwen: Qwen3 VL 32B Instruct if…
cost matters at scale — it is 55% cheaper on a typical 3:1 input/output mix ($16.12 vs $35.00 a month for 50,000 support chats)
you need log-probabilities — to read token confidence for classification and scoring; Mistral: Mistral Medium 3.1 (batch) does not advertise it
Frequently asked questions
Is Mistral: Mistral Medium 3.1 (batch) better than Qwen: Qwen3 VL 32B Instruct?
Neither wins outright: Mistral: Mistral Medium 3.1 (batch) is the pick when you need file / PDF input, Qwen: Qwen3 VL 32B Instruct when cost matters at scale. In short: Mistral: Mistral Medium 3.1 (batch) when you need file / PDF input, you generate long outputs in one go; Qwen: Qwen3 VL 32B Instruct when cost matters at scale, you need log-probabilities.
Which is cheaper, Mistral: Mistral Medium 3.1 (batch) or Qwen: Qwen3 VL 32B Instruct?
Qwen: Qwen3 VL 32B Instruct is cheaper: $0.18 vs $0.40 per 1M tokens at a typical 3:1 input/output mix, 55% less. For 50,000 support conversations a month that is $16.12 against $35.00.
How much do Mistral: Mistral Medium 3.1 (batch) and Qwen: Qwen3 VL 32B Instruct cost per million tokens?
Mistral: Mistral Medium 3.1 (batch) costs $0.20 per 1M input tokens and $1.00 per 1M output tokens; Qwen: Qwen3 VL 32B Instruct costs $0.10 input and $0.42 output. Output tokens are billed separately, so long answers shift the gap.
Which has the bigger context window, Mistral: Mistral Medium 3.1 (batch) or Qwen: Qwen3 VL 32B Instruct?
Both take 131K tokens per request — roughly 197 pages of text.
Do Mistral: Mistral Medium 3.1 (batch) and Qwen: Qwen3 VL 32B Instruct support function calling and JSON output?
Can Mistral: Mistral Medium 3.1 (batch) or Qwen: Qwen3 VL 32B Instruct read images?
Yes, both accept image input.
Is Mistral: Mistral Medium 3.1 (batch) or Qwen: Qwen3 VL 32B Instruct free to use?
No free variant is listed for either; both are pay-per-token.
What is the maximum output length of Mistral: Mistral Medium 3.1 (batch) and Qwen: Qwen3 VL 32B Instruct?
Mistral: Mistral Medium 3.1 (batch) can write up to 105K tokens (about 78,600 words) per response; Qwen: Qwen3 VL 32B Instruct up to 33K (about 24,600 words).
When were Mistral: Mistral Medium 3.1 (batch) and Qwen: Qwen3 VL 32B Instruct released?
Mistral: Mistral Medium 3.1 (batch) was listed on 2025-08-13; Qwen: Qwen3 VL 32B Instruct on 2025-10-23.
Has the price of Mistral: Mistral Medium 3.1 (batch) or Qwen: Qwen3 VL 32B Instruct changed?
Mistral: Mistral Medium 3.1 (batch): input price cut 50% ($0.40 → $0.20/1M), output price cut 50% ($2.00 → $1.00/1M) on 2026-09-10. Qwen: Qwen3 VL 32B Instruct: price unchanged since we started tracking it on 2026-03-10.
Mistral Medium 3.1 is an updated version of Mistral Medium 3, which is a high-performance enterprise-grade language model designed to deliver frontier-level capabilities at significantly reduced operational cost. It balances...
Qwen3-VL-32B-Instruct is a large-scale multimodal vision-language model designed for high-precision understanding and reasoning across text, images, and video. With 32 billion parameters, it combines deep visual perception with advanced text...