Mistral Large 3 2512 vs GPT-5.2 Pro
Mistral AIOpenAIboth via one key, provider price + 3%
Mistral Large 3 2512 and GPT-5.2 Pro sit at opposite ends of the price-performance curve. One is a 675B-parameter (41B active) mixture-of-experts model released under Apache 2.0, priced for scale. The other is OpenAI's most expensive current model, built for agentic coding and reasoning depth over long context. Both run on OpenKey with one API key and a flat 3% fee over provider list price — this page breaks down where each one actually wins.
Spec vs spec
| Spec | Mistral Large 3 2512 | GPT-5.2 Pro |
|---|---|---|
| Context window | 262K | 400K |
| Max output | — | 128K |
| Input modalities | text, image, file | image, text, file |
| Output modalities | text | text |
| Released | Dec 1, 2025 | Dec 10, 2025 |
| Reasoning | — | always on |
Pricing
Per 1M tokens. Provider price plus the flat 3% fee — the sum is what you pay.
mistralai/mistral-large-2512
Input · 1M tokens
$0.500 + 3%$0.515
Output · 1M tokens
$1.50 + 3%$1.54
Cache read · 1M tokens
$0.050 + 3%$0.052
FEE — FLAT, EVERY MODEL3%
openai/gpt-5.2-pro
Input · 1M tokens
$21.00 + 3%$21.63
Output · 1M tokens
$168.00 + 3%$173.04
FEE — FLAT, EVERY MODEL3%
One workload, priced on both
10M input + 2M output tokens at each model's price, flat 3% fee included.
mistralai/mistral-large-2512Cheaper
$8.24
$8.00 provider + 3%
openai/gpt-5.2-pro
$562.38
$546.00 provider + 3%
Pricing math: what a real workload costs
Take a workload of 10M input tokens and 2M output tokens — a reasonable stand-in for a batch job or a day of moderate agent traffic.
Mistral Large 3 2512: provider price is $0.50/M input, $1.50/M output. On OpenKey that's $0.515/M input and $1.545/M output (price × 1.03). Total workload cost: **$8.00**.
GPT-5.2 Pro: provider price is $21.00/M input, $168.00/M output. On OpenKey that's $21.63/M input and $173.04/M output. Total workload cost: **$546.00**.
That's a 68x cost gap for the same token counts. The input price ratio alone is 0.02 — GPT-5.2 Pro's input tokens cost roughly 50x more than Mistral's. If your workload is cost-sensitive or high-volume, this number alone should end the debate.
Coding and agentic performance
Mistral Large 3 2512 has published Artificial Analysis scores: an intelligence index of 15.9, a coding index of 20.1, and an agentic index of 5.5. Its Design Arena numbers show it ranked 56th in codecategories (elo 1191, 47.6% win rate) and 65th in gamedev (elo 1146, 41.5% win rate) — mid-pack among ranked models, not a leader.
GPT-5.2 Pro has no benchmark data in this dataset, but its architecture signals what it's built for: mandatory reasoning with effort levels up to "xhigh," and OpenAI's own description centers it on "agentic coding and long context performance." Without published benchmark numbers here, treat that as a directional claim, not a scored one — but the reasoning-effort parameter alone matters for multi-step coding tasks that Mistral's parameter set doesn't expose.
Context and long-document work
GPT-5.2 Pro supports 400,000 tokens of context and 128,000 max output tokens. Mistral Large 3 2512 supports 262,144 tokens of context with no stated max output cap in this data. The context ratio is 0.66 — Mistral's window is about two-thirds the size of GPT-5.2 Pro's.
For most document-analysis or codebase-review tasks, 262K tokens is still large enough to hold a mid-size repo or a long report. But if you're routinely pushing near the edge of context — very long transcripts, multi-file agent sessions, or extended chat history — GPT-5.2 Pro's larger window and explicit 128K output cap give you more headroom before you have to chunk or summarize.
When to pick each
Pick Mistral Large 3 2512 when you're running high request volume, iterating fast, or building anything where per-token cost compounds — batch pipelines, internal tools, high-frequency agent loops. Its Apache 2.0 license and open architecture also matter if you need to self-host or audit weights later.
Pick GPT-5.2 Pro when the task is genuinely hard: multi-step agentic coding, tasks that benefit from "xhigh" reasoning effort, or workloads where the 400K context window is the limiting factor. It's not a model to route casual traffic through — at $173.04/M output tokens on OpenKey, a single long-output run adds up fast.
Which model for which job
| Use case | Pick | Why |
|---|---|---|
| High-volume batch processing | Mistral Large 3 2512 | Costs $8.00 vs $546.00 for the same 10M-in/2M-out workload |
| Long-context document analysis | GPT-5.2 Pro | 400,000 token context vs Mistral's 262,144 |
| Complex multi-step agentic coding | GPT-5.2 Pro | Mandatory reasoning with configurable effort up to xhigh |
| Self-hosted or license-flexible deployment | Mistral Large 3 2512 | Released under Apache 2.0 |
| Budget-constrained prototyping | Mistral Large 3 2512 | Input tokens priced at $0.515/M on OpenKey vs $21.63/M |
| Tasks needing max single-response output | GPT-5.2 Pro | 128,000 max completion tokens stated explicitly; Mistral has none listed |
Questions
- How much cheaper is Mistral Large 3 2512 than GPT-5.2 Pro?
- On a 10M input / 2M output token workload, Mistral Large 3 2512 costs $8.00 on OpenKey versus $546.00 for GPT-5.2 Pro — a roughly 68x difference. The gap comes mostly from output pricing: $1.545/M vs $173.04/M.
- Which model has the bigger context window?
- GPT-5.2 Pro supports 400,000 tokens of context, compared to 262,144 for Mistral Large 3 2512. That puts the context ratio at 0.66 — Mistral holds about two-thirds as much context as GPT-5.2 Pro.
- Does Mistral Large 3 2512 have published benchmark scores?
- Yes. It has an Artificial Analysis intelligence index of 15.9, coding index of 20.1, and agentic index of 5.5, plus Design Arena rankings across eight categories including codecategories (rank 56, elo 1191) and website (rank 53, elo 1205). GPT-5.2 Pro has no benchmark data in this dataset.
- Can I use both models through the same API key?
- Yes. Both Mistral Large 3 2512 and GPT-5.2 Pro are available on OpenKey with one API key across the full catalog, and pricing is provider list price plus a flat 3% fee — for example GPT-5.2 Pro's $21.00/M input becomes $21.63/M on OpenKey.