Neither wins outright: Mistral: Mistral Large 3 2512 is the pick when cost matters at scale, Pareto 26.9 when you want the newer model.
| Spec | Mistral: Mistral Large 3 2512 | Pareto 26.9 |
|---|---|---|
| Provider | Mistral AI | Unbiased |
| Input price (per 1M tokens) | $0.50 | $2.50 |
| Output price (per 1M tokens) | $1.50 | $7.50 |
| Blended price (3:1 input/output) | $0.75 | $3.75 |
| Cheaper than … of all models we track | 45% | 17% |
| Context window | 262K tokens (~393 pages) | 262K tokens (~393 pages) |
| Larger context than … of all models | 48% | 48% |
| Max output per response | 210K tokens (~157,300 words) | 131K tokens (~98,300 words) |
| Input types | text, image, file | text, image |
| Output types | text | text |
| Free variant | No | No |
| Listed since | 2025-12-01 | 2026-10-13 |
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 | Pareto 26.9 | Difference |
|---|---|---|---|
| Customer-support chatbot 50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens) | $67.50 | $338 | Mistral: Mistral Large 3 2512 saves $270 |
| RAG search over documents 20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens) | $75.00 | $375 | Mistral: Mistral Large 3 2512 saves $300 |
| 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) | $78.00 | $390 | Mistral: Mistral Large 3 2512 saves $312 |
| Batch summarisation 10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens) | $49.00 | $245 | Mistral: Mistral Large 3 2512 saves $196 |
| Long-document analysis 500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens) | $26.50 | $133 | Mistral: Mistral Large 3 2512 saves $106 |
| Capability | Mistral: Mistral Large 3 2512 | Pareto 26.9 | 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 | — | 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.
Neither wins outright: Mistral: Mistral Large 3 2512 is the pick when cost matters at scale, Pareto 26.9 when you want the newer model. In short: Mistral: Mistral Large 3 2512 when cost matters at scale, you need file / PDF input, you need seed (reproducible sampling), you generate long outputs in one go; Pareto 26.9 when you want the newer model.
Mistral: Mistral Large 3 2512 is cheaper: $0.75 vs $3.75 per 1M tokens at a typical 3:1 input/output mix, 80% less. For 50,000 support conversations a month that is $67.50 against $338.
Mistral: Mistral Large 3 2512 costs $0.50 per 1M input tokens and $1.50 per 1M output tokens; Pareto 26.9 costs $2.50 input and $7.50 output. Output tokens are billed separately, so long answers shift the gap.
Both take 262K tokens per request — roughly 393 pages of text.
Tool calling — Mistral: Mistral Large 3 2512: yes, Pareto 26.9: yes. JSON-schema structured output — Mistral: Mistral Large 3 2512: yes, Pareto 26.9: yes.
Yes, both accept image input.
No free variant is listed for either; both are pay-per-token.
Mistral: Mistral Large 3 2512 can write up to 210K tokens (about 157,300 words) per response; Pareto 26.9 up to 131K (about 98,300 words).
Mistral: Mistral Large 3 2512 was listed on 2025-12-01; Pareto 26.9 on 2026-10-13.
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 specs →Pareto is a multimodal composite model built for research, coding, and agentic workflows, while delivering frontier-level performance across a broad range of general-purpose tasks.
Full Pareto 26.9 specs →