Llama 3.1 Euryale 70B v2.2 vs Hy4 preview
Llama 3.1 Euryale 70B v2.2 costs 2.9x less per output token than Hy4 preview ($0.85 vs $2.501 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.85
- Coding
- 44.3
- Overall
- No data
- Output $/M
- $2.501
Llama 3.1 Euryale 70B v2.2 or Hy4 preview: which to pick
Only Hy4 preview has a coding score, 44.3 on the Vibe Coding Index; Llama 3.1 Euryale 70B v2.2 has none, so the two cannot be ranked on coding.
Pick Llama 3.1 Euryale 70B v2.2 for output tokens 2.9x cheaper ($0.85 vs $2.501 per million).
No benchmark has tested both yet. Llama 3.1 Euryale 70B v2.2 has none yet; Hy4 preview on LMArena WebDev, Terminal-Bench 4 (Vals AI) and Vibe Code Bench (Vals AI). 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
Only Hy4 preview has a coding score, so no call is made.
One side not measured
General
Vals Index
No call
Only Hy4 preview has a Vals Index result, 53.2%.
Directional only
Long documents
Listed context window
Hy4 preview
Hy4 preview 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, Hy4 preview $0.0021 per turn.
List prices
At a glance
- Coding index
- Llama 3.1 Euryale 70B v2.2 not benchmarked, Hy4 preview 44.3 from 3 benchmarks.
- 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 Hy4 preview $2.501 per million output tokens, 2.9x apart.
- Context window
- Llama 3.1 Euryale 70B v2.2 takes 131K tokens, Hy4 preview 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.
CodingDirectional onlySix of these boards feed the Vibe Coding Index10 boards measured
| Benchmark | Llama 3.1 Euryale 70B v2.2 | Hy4 preview | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1631 | Only Hy4 preview measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 8.1% | Only Hy4 preview measured |
| Vibe Code Bench (Vals AI) | Not measured | 77.5% | Only Hy4 preview measured |
| Code migration (Vals AI) | Not measured | 47.4% | Only Hy4 preview measured |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only Hy4 preview measured |
| IOI (Vals AI) | Not measured | 59.3% | Only Hy4 preview measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 55.1% | Only Hy4 preview measured |
| CyberBench (Vals AI) | Not measured | 65.4% | Only Hy4 preview measured |
| LMArena WebDev: React | Not measured | 1653 | Only Hy4 preview measured |
| LMArena WebDev: HTML | Not measured | 1620 | Only Hy4 preview measured |
| Neither model has a result on the other 33 boards here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index8 boards measured
| Benchmark | Llama 3.1 Euryale 70B v2.2 | Hy4 preview | Leader |
|---|---|---|---|
| SREBench (Vals AI) | Not measured | 2.3% | Only Hy4 preview measured |
| Finance Agent (Vals AI) | Not measured | 55.1% | Only Hy4 preview measured |
| Tax Agent Bench (Vals AI) | Not measured | 32.6% | Only Hy4 preview measured |
| Legal Research Bench (Vals AI) | Not measured | 45.2% | Only Hy4 preview measured |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 8.8% | Only Hy4 preview measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 58.1% | Only Hy4 preview measured |
| BioMysteryBench (Vals AI) | Not measured | 69.3% | Only Hy4 preview measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 1.4% | Only Hy4 preview measured |
| Neither model has a result on the other 34 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Llama 3.1 Euryale 70B v2.2 | Hy4 preview | Leader |
|---|---|---|---|
| ProofBench | Not measured | 75.0% | Only Hy4 preview measured |
| Neither model has a result on the other 13 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Llama 3.1 Euryale 70B v2.2 | Hy4 preview | Leader |
|---|---|---|---|
| LegalBench (Vals AI) | Not measured | 83.8% | Only Hy4 preview measured |
| MedCode (Vals AI) | Not measured | 43.3% | Only Hy4 preview measured |
| Neither model has a result on the other 18 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | Llama 3.1 Euryale 70B v2.2 | Hy4 preview | Leader |
|---|---|---|---|
| Vals Index | Not measured | 53.2% | Only Hy4 preview measured |
| Public Benefits Bench (Vals AI) | Not measured | 68.6% | Only Hy4 preview measured |
| MedScribe (Vals AI) | Not measured | 83.6% | Only Hy4 preview 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
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 | Tencent Hy4 preview |
|---|---|---|
| Maker | Sao10K | Tencent |
| Weights | Open weights | Open weights |
| Released | August 28, 2024 | August 28, 2026 |
| Context window | 131K | 1.05M |
| Input $/Mtok | $0.85 | $0.834 |
| Output $/Mtok | $0.85 | $2.501 |
| Coding index | Not benchmarked | 44.3 |
| Independent measurements behind it | 0 | 3 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Llama 3.1 Euryale 70B v2.2 better than Hy4 preview for coding?
Only Hy4 preview has a coding score, 44.3 on the Vibe Coding Index; Llama 3.1 Euryale 70B v2.2 has none, so the two cannot be ranked on coding. Pick Llama 3.1 Euryale 70B v2.2 for output tokens 2.9x cheaper ($0.85 vs $2.501 per million).
Which is cheaper, Llama 3.1 Euryale 70B v2.2 or Hy4 preview?
Llama 3.1 Euryale 70B v2.2 costs $0.85 per million input tokens and $0.85 per million output tokens; Hy4 preview costs $0.834 and $2.501. Cost per solved task is known for neither of them.
Which has the bigger context window, Llama 3.1 Euryale 70B v2.2 or Hy4 preview?
Hy4 preview, with 1.05M tokens against 131K.
Has any benchmark tested both Llama 3.1 Euryale 70B v2.2 and Hy4 preview?
No benchmark has tested both yet. Llama 3.1 Euryale 70B v2.2 has none yet; Hy4 preview on LMArena WebDev, Terminal-Bench 4 (Vals AI) and Vibe Code Bench (Vals AI). Compare them on price and context instead. Data as of October 22, 2026.