Mistral Nemo vs Llama 3.1 Euryale 70B v2.2
Mistral Nemo costs 5.7x less per output token than Llama 3.1 Euryale 70B v2.2 ($0.15 vs $0.85 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.15
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.85
Mistral Nemo or Llama 3.1 Euryale 70B v2.2: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Mistral Nemo for output tokens 5.7x cheaper ($0.15 vs $0.85 per million).
No benchmark has tested both yet. Mistral Nemo has results on Epoch Capabilities Index, MMLU and DTBench; Llama 3.1 Euryale 70B v2.2 has none yet. Compare them on price and context instead.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Long documents
Listed context window
No call
Both take 131K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Nemo
Mistral Nemo $0.0002, Llama 3.1 Euryale 70B v2.2 $0.0013 per turn.
List prices
At a glance
- Coding index
- Mistral Nemo not benchmarked, Llama 3.1 Euryale 70B v2.2 not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- Mistral Nemo $0.15 against Llama 3.1 Euryale 70B v2.2 $0.85 per million output tokens, 5.7x apart.
- Context window
- Both take 131K tokens.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Mistral Nemo | Llama 3.1 Euryale 70B v2.2 | Leader |
|---|---|---|---|
| Epoch Capabilities Index | 118.7 | Not measured | Only Mistral Nemo measured |
| Neither model has a result on the other 1 board here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Mistral Nemo | Llama 3.1 Euryale 70B v2.2 | Leader |
|---|---|---|---|
| MMLU | 65.3% | Not measured | Only Mistral Nemo measured |
| Neither model has a result on the other 17 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Mistral Nemo | Llama 3.1 Euryale 70B v2.2 | Leader |
|---|---|---|---|
| DTBench | 48.6% | Not measured | Only Mistral Nemo measured |
| Neither model has a result on the other 45 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Mistral Nemo costs less
Repository review
50K input + 3K output tokens
Mistral Nemo costs less
Agent loop
200K input + 10K output tokens
Mistral Nemo costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | Mistral Nemo | Sao10K Llama 3.1 Euryale 70B v2.2 |
|---|---|---|
| Maker | Mistral AI | Sao10K |
| Weights | Open weights | Open weights |
| Released | July 19, 2024 | August 28, 2024 |
| Context window | 131K | 131K |
| Input $/Mtok | $0.15 | $0.85 |
| Output $/Mtok | $0.15 | $0.85 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mistral Nemo better than Llama 3.1 Euryale 70B v2.2 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Mistral Nemo for output tokens 5.7x cheaper ($0.15 vs $0.85 per million).
Which is cheaper, Mistral Nemo or Llama 3.1 Euryale 70B v2.2?
Mistral Nemo costs $0.15 per million input tokens and $0.15 per million output tokens; Llama 3.1 Euryale 70B v2.2 costs $0.85 and $0.85. Cost per solved task is known for neither of them.
Which has the bigger context window, Mistral Nemo or Llama 3.1 Euryale 70B v2.2?
Neither: both take 131K tokens.
Has any benchmark tested both Mistral Nemo and Llama 3.1 Euryale 70B v2.2?
No benchmark has tested both yet. Mistral Nemo has results on Epoch Capabilities Index, MMLU and DTBench; Llama 3.1 Euryale 70B v2.2 has none yet. Compare them on price and context instead. Data as of October 22, 2026.