Choose Mistral: Mistral Large 3 2512 (batch) if…
- you generate long outputs in one go — up to 210K tokens (about 157,300 words) per response
- you want the newer model — released 2025-12-01, 4 months after the other
Mistral: Mistral Large 3 2512 (batch) vs OpenAI: GPT-5 Nano (batch)
Neither wins outright: Mistral: Mistral Large 3 2512 (batch) is the pick when you generate long outputs in one go, OpenAI: GPT-5 Nano (batch) when cost matters at scale.
Key numbers
| Spec | Mistral: Mistral Large 3 2512 (batch) | OpenAI: GPT-5 Nano (batch) |
|---|---|---|
| Provider | Mistral AI | OpenAI |
| Input price (per 1M tokens) | $0.25 | $0.03 |
| Output price (per 1M tokens) | $0.75 | $0.20 |
| Blended price (3:1 input/output) | $0.38 | $0.07 |
| Cheaper than … of all models we track | 59% | 84% |
| Context window | 262K tokens (~393 pages) | 400K tokens (~600 pages) |
| Larger context than … of all models | 48% | 63% |
| Max output per response | 210K tokens (~157,300 words) | 128K tokens (~96,000 words) |
| Input types | text, image, file | text, image, file |
| Output types | text | text |
| Free variant | No | No |
| Listed since | 2025-12-01 | 2025-08-07 |
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What it costs for real workloads
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 Large 3 2512 (batch) | OpenAI: GPT-5 Nano (batch) | Difference |
|---|---|---|---|
| Customer-support chatbot 50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens) | $33.75 | $5.88 | OpenAI: GPT-5 Nano (batch) saves $27.88 |
| RAG search over documents 20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens) | $37.50 | $5.00 | OpenAI: GPT-5 Nano (batch) saves $32.50 |
| 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) | $39.00 | $5.40 | OpenAI: GPT-5 Nano (batch) saves $33.60 |
| Batch summarisation 10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens) | $24.50 | $3.20 | OpenAI: GPT-5 Nano (batch) saves $21.30 |
| Long-document analysis 500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens) | $13.25 | $1.45 | OpenAI: GPT-5 Nano (batch) saves $11.80 |
Capabilities side by side
| Capability | Mistral: Mistral Large 3 2512 (batch) | OpenAI: GPT-5 Nano (batch) | 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 | — | ✓ Yes | 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 | ✓ Yes | accept documents without your own parsing step |
| Image output | — | — | generate images, not just text |
| Built-in web search | — | ✓ Yes | answer from live web results |
| Seed (reproducible sampling) | ✓ Yes | ✓ Yes | repeat a generation for tests and evals |
| Log-probabilities | — | — | read token confidence for classification and scoring |
From each model's published parameters and input/output types. “—” means not advertised, not proven absent.
Price history
- Mistral: Mistral Large 3 2512 (batch): input price cut 50% ($0.50 → $0.25/1M), output price cut 50% ($1.50 → $0.75/1M) on 2026-09-10.
- OpenAI: GPT-5 Nano (batch): price unchanged since we started tracking it on 2026-08-07.
| Date | Model | Input / 1M | Output / 1M |
|---|---|---|---|
| 2026-09-10 | Mistral: Mistral Large 3 2512 (batch) | $0.25 | $0.75 |
Which should you choose?
Choose OpenAI: GPT-5 Nano (batch) if…
- cost matters at scale — it is 82% cheaper on a typical 3:1 input/output mix ($5.88 vs $33.75 a month for 50,000 support chats)
- you need to fit long inputs in one request — 400K tokens is roughly 600 pages, against 393
- you need reasoning / thinking mode — to spend extra tokens thinking before answering hard problems; Mistral: Mistral Large 3 2512 (batch) does not advertise it
- you need built-in web search — to answer from live web results; Mistral: Mistral Large 3 2512 (batch) does not advertise it
Frequently asked questions
Is Mistral: Mistral Large 3 2512 (batch) better than OpenAI: GPT-5 Nano (batch)?
Neither wins outright: Mistral: Mistral Large 3 2512 (batch) is the pick when you generate long outputs in one go, OpenAI: GPT-5 Nano (batch) when cost matters at scale. In short: Mistral: Mistral Large 3 2512 (batch) when you generate long outputs in one go, you want the newer model; OpenAI: GPT-5 Nano (batch) when cost matters at scale, you need to fit long inputs in one request, you need reasoning / thinking mode, you need built-in web search.
Which is cheaper, Mistral: Mistral Large 3 2512 (batch) or OpenAI: GPT-5 Nano (batch)?
OpenAI: GPT-5 Nano (batch) is cheaper: $0.07 vs $0.38 per 1M tokens at a typical 3:1 input/output mix, 82% less. For 50,000 support conversations a month that is $5.88 against $33.75.
How much do Mistral: Mistral Large 3 2512 (batch) and OpenAI: GPT-5 Nano (batch) cost per million tokens?
Mistral: Mistral Large 3 2512 (batch) costs $0.25 per 1M input tokens and $0.75 per 1M output tokens; OpenAI: GPT-5 Nano (batch) costs $0.03 input and $0.20 output. Output tokens are billed separately, so long answers shift the gap.
Which has the bigger context window, Mistral: Mistral Large 3 2512 (batch) or OpenAI: GPT-5 Nano (batch)?
OpenAI: GPT-5 Nano (batch): 400K tokens, about 600 pages, against 262K (about 393 pages) for Mistral: Mistral Large 3 2512 (batch).
Do Mistral: Mistral Large 3 2512 (batch) and OpenAI: GPT-5 Nano (batch) support function calling and JSON output?
Tool calling — Mistral: Mistral Large 3 2512 (batch): yes, OpenAI: GPT-5 Nano (batch): yes. JSON-schema structured output — Mistral: Mistral Large 3 2512 (batch): yes, OpenAI: GPT-5 Nano (batch): yes.
Can Mistral: Mistral Large 3 2512 (batch) or OpenAI: GPT-5 Nano (batch) read images?
Yes, both accept image input.
Is Mistral: Mistral Large 3 2512 (batch) or OpenAI: GPT-5 Nano (batch) free to use?
No free variant is listed for either; both are pay-per-token.
What is the maximum output length of Mistral: Mistral Large 3 2512 (batch) and OpenAI: GPT-5 Nano (batch)?
Mistral: Mistral Large 3 2512 (batch) can write up to 210K tokens (about 157,300 words) per response; OpenAI: GPT-5 Nano (batch) up to 128K (about 96,000 words).
When were Mistral: Mistral Large 3 2512 (batch) and OpenAI: GPT-5 Nano (batch) released?
Mistral: Mistral Large 3 2512 (batch) was listed on 2025-12-01; OpenAI: GPT-5 Nano (batch) on 2025-08-07.
Has the price of Mistral: Mistral Large 3 2512 (batch) or OpenAI: GPT-5 Nano (batch) changed?
Mistral: Mistral Large 3 2512 (batch): input price cut 50% ($0.50 → $0.25/1M), output price cut 50% ($1.50 → $0.75/1M) on 2026-09-10. OpenAI: GPT-5 Nano (batch): price unchanged since we started tracking it on 2026-08-07.
About the two models
Mistral: Mistral Large 3 2512 (batch)
Mistral Large 3 2512 is Mistral’s most capable model to date, featuring a sparse mixture-of-experts architecture with 41B active parameters (675B total), and released under the Apache 2.0 license.
Full Mistral: Mistral Large 3 2512 (batch) specs →OpenAI: GPT-5 Nano (batch)
GPT-5-Nano is the smallest and fastest variant in the GPT-5 system, optimized for developer tools, rapid interactions, and ultra-low latency environments. While limited in reasoning depth compared to its larger...
Full OpenAI: GPT-5 Nano (batch) specs →