Llama 3.1 Euryale 70B v2.2 vs Pareto 26.10
Llama 3.1 Euryale 70B v2.2 costs 3.8x less per output token than Pareto 26.10 ($0.85 vs $3.20 per million). Updated October 23, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.85
- Coding
- No data
- Overall
- No data
- Output $/M
- $3.20
Llama 3.1 Euryale 70B v2.2 or Pareto 26.10: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Llama 3.1 Euryale 70B v2.2 for output tokens 3.8x cheaper ($0.85 vs $3.20 per million).
No benchmark has tested either model yet, so price and context are the only way to compare them.
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
Pareto 26.10
Pareto 26.10 takes 1.05M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Llama 3.1 Euryale 70B v2.2
Llama 3.1 Euryale 70B v2.2 $0.0013, Pareto 26.10 $0.0024 per turn.
List prices
At a glance
- Coding index
- Llama 3.1 Euryale 70B v2.2 not benchmarked, Pareto 26.10 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
- Llama 3.1 Euryale 70B v2.2 $0.85 against Pareto 26.10 $3.20 per million output tokens, 3.8x apart.
- Context window
- Llama 3.1 Euryale 70B v2.2 takes 131K tokens, Pareto 26.10 1.05M.
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.
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
Llama 3.1 Euryale 70B v2.2 costs less
Repository review
50K input + 3K output tokens
Llama 3.1 Euryale 70B v2.2 costs less
Agent loop
200K input + 10K output tokens
Llama 3.1 Euryale 70B v2.2 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 | Sao10K Llama 3.1 Euryale 70B v2.2 | Pareto 26.10 |
|---|---|---|
| Maker | Sao10K | Unbiased |
| Weights | Open weights | No public weights listed |
| Released | August 28, 2024 | October 15, 2026 |
| Context window | 131K | 1.05M |
| Input $/Mtok | $0.85 | $0.80 |
| Output $/Mtok | $0.85 | $3.20 |
| 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 Llama 3.1 Euryale 70B v2.2 better than Pareto 26.10 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Llama 3.1 Euryale 70B v2.2 for output tokens 3.8x cheaper ($0.85 vs $3.20 per million).
Which is cheaper, Llama 3.1 Euryale 70B v2.2 or Pareto 26.10?
Llama 3.1 Euryale 70B v2.2 costs $0.85 per million input tokens and $0.85 per million output tokens; Pareto 26.10 costs $0.80 and $3.20. Cost per solved task is known for neither of them.
Which has the bigger context window, Llama 3.1 Euryale 70B v2.2 or Pareto 26.10?
Pareto 26.10, with 1.05M tokens against 131K.
Has any benchmark tested both Llama 3.1 Euryale 70B v2.2 and Pareto 26.10?
No benchmark has tested either model yet, so price and context are the only way to compare them. Data as of October 23, 2026.