// head_to_head
Claude Opus 5.5 vs Mistral Nemo
Published LiveBench scores across all seven categories, live list pricing, context windows, and the measured cost of a point of capability — for both models, side by side.
Mistral Nemo is the cheaper of the two; neither can be ranked on quality here.
Mistral Nemo does not have a published LiveBench run, so this comparison covers price, context and declared capabilities only. A missing score means "not evaluated", not "worse" — the right way to separate these two is an eval on your own workload.
anthropic
Claude Opus 5.5
- Blended / 1M
- $8.00
- Context
- 1M
- Released
- Sep 22, 2026
- Overall score
- 83.2
mistralai
Mistral Nemo
- Blended / 1M
- $0.022
- Context
- 131K
- Released
- Jul 19, 2024
- Overall score
- Not evaluated
Specs and pricing
| Metric | Claude Opus 5.5 | Mistral Nemo |
|---|---|---|
| LiveBench overall Mean of the seven LiveBench category scores, 0–100. Higher is better. | 83.2 | — |
| Cost per point Measured benchmark spend divided by overall score — dollars per point of capability. | $0.4474 | — |
| Blended price / 1M 3:1 input:output mix, the usual shape of production traffic. | $8.00 | $0.022win |
| Input price / 1M | $4.00 | $0.019win |
| Output price / 1M | $20.00 | $0.030win |
| Cached input / 1M Price of an input token served from the prompt cache, where the provider publishes one. | $0.200 | — |
| Context window | 1Mwin | 131K |
| Max output tokens | 128Kwin | 16K |
Benchmarks by category
An overall score averages away the thing you probably care about. These are the seven LiveBench categories scored separately — Claude Opus 5.5 on top, Mistral Nemo below, both out of 100.
What each one costs to run
Per-token prices are hard to feel. These are monthly list costs for both models across five workload shapes, using each provider's published cached-input rate where there is one.
| Workload | Claude Opus 5.5 | Mistral Nemo |
|---|---|---|
| Support chatbot 1.2K in / 400 out × 200K requests | $2,286/mo | $6.96/mo |
| RAG assistant 8K in / 600 out × 100K requests | $2,880/mo | $17.00/mo |
| Coding agent 40K in / 4K out × 20K requests | $2,672/mo | $17.60/mo |
| Document extraction 20K in / 1.5K out × 50K requests | $5,310/mo | $21.25/mo |
| Bulk classification 500 in / 20 out × 5M requests | $10,100/mo | $50.50/mo |
Which should you pick?
You need to fit large documents in one call
Claude Opus 5.5
Wider context window — 1M against 131K.
You are cost-constrained
Mistral Nemo
Cheaper on blended list price at $0.022 per million tokens.
Claude Opus 5.5 vs Mistral Nemo FAQ
Which is better, Claude Opus 5.5 or Mistral Nemo?
Mistral Nemo is the cheaper of the two; neither can be ranked on quality here. Mistral Nemo does not have a published LiveBench run, so this comparison covers price, context and declared capabilities only. A missing score means "not evaluated", not "worse" — the right way to separate these two is an eval on your own workload.
Is Claude Opus 5.5 cheaper than Mistral Nemo?
Mistral Nemo is cheaper. On a 3:1 input:output blend, Claude Opus 5.5 lists at $8.00 per million tokens and Mistral Nemo at $0.022 — Mistral Nemo is 368× cheaper. Input and output are priced separately — Claude Opus 5.5 charges $4.00 in and $20.00 out, Mistral Nemo charges $0.019 and $0.030 — so the model that looks cheaper flips depending on how output-heavy your workload is.
Does Claude Opus 5.5 or Mistral Nemo have a bigger context window?
Claude Opus 5.5 has the larger context window: 1M for Claude Opus 5.5 against 131K for Mistral Nemo. Note that a window you can fill is not a window you should fill — retrieval quality usually degrades well before the limit, and you pay for every token you put in it.
Do Claude Opus 5.5 and Mistral Nemo support prompt caching?
Claude Opus 5.5 publishes a cached-input rate of $0.200 per million tokens against a full input rate of $4.00. The catalogue lists no separate cached rate for Mistral Nemo, which means the provider does not price it separately here — not that caching is unavailable.
Related comparisons
How these numbers are produced
- Price — provider list price from OpenRouter, refreshed every 15 minutes. “Blended” is a 3:1 input:output mix.
- Scores — LiveBench release 2026-06-25, using their own category map. Each model shows its strongest published run. A blank means “not evaluated”, never “bad”.
- Cost per point — the measured dollars LiveBench spent on the run, divided by the score it earned.
- “Win” — awarded only past a threshold: one full point on a benchmark score, 10% on a price, 25% on a context window. Anything tighter reports as a tie, because effort settings alone move a LiveBench score by more than that.
Published benchmarks rank models on someone else's tasks. Before committing, see LLM & agent evaluation for building an eval on your own.