Llama 3.3 Euryale 70B vs Hy4
Llama 3.3 Euryale 70B costs 1.7x less per output token than Hy4 ($0.75 vs $1.2505 per million). Updated November 14, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.75
- Coding
- 65.2
- Overall
- No data
- Output $/M
- $1.2505
Llama 3.3 Euryale 70B or Hy4: which to pick
Only Hy4 has a coding score, 65.2 on the Vibe Coding Index; Llama 3.3 Euryale 70B has none, so the two cannot be ranked on coding.
Pick Llama 3.3 Euryale 70B for output tokens 1.7x cheaper ($0.75 vs $1.2505 per million).
No benchmark has tested both yet. Llama 3.3 Euryale 70B has none yet; Hy4 on Terminal-Bench 4 (Vals AI), Vibe Code Bench (Vals AI) and Terminal-Bench 4.0 (Artificial Analysis run). 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 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Hy4 has a AA Intelligence Index result, 34.6.
Directional only
Web design
Design Arena: websites
No call
Only Hy4 has a Design Arena: websites result, 1251.
Directional only
General
Vals Index
No call
Only Hy4 has a Vals Index result, 59.4%.
Directional only
Long documents
Listed context window
Hy4
Hy4 takes 1.05M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Llama 3.3 Euryale 70B
Llama 3.3 Euryale 70B $0.0010, Hy4 $0.0010 per turn.
List prices
At a glance
- Coding index
- Llama 3.3 Euryale 70B not benchmarked, Hy4 65.2 from 2 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 3.3 Euryale 70B $0.75 against Hy4 $1.2505 per million output tokens, 1.7x apart.
- Context window
- Llama 3.3 Euryale 70B takes 131K tokens, Hy4 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 Index6 boards measured
| Benchmark | Llama 3.3 Euryale 70B | Hy4 | Leader |
|---|---|---|---|
| Terminal-Bench 4 (Vals AI) | Not measured | 39.4% | Only Hy4 measured |
| Vibe Code Bench (Vals AI) | Not measured | 81.0% | Only Hy4 measured |
| Terminal-Bench 4.0 (Artificial Analysis run) | Not measured | 37.4% | Only Hy4 measured |
| FrontierCode 2.0 | Not measured | 31.4% | Only Hy4 measured |
| GameBench 2 | Not measured | 48.7 | Only Hy4 measured |
| Terminal-Bench 4.0 | Not measured | 39.1% | Only Hy4 measured |
| Neither model has a result on the other 46 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Llama 3.3 Euryale 70B | Hy4 | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 34.6 | Only Hy4 measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | Llama 3.3 Euryale 70B | Hy4 | Leader |
|---|---|---|---|
| Tax Agent Bench (Vals AI) | Not measured | 34.4% | Only Hy4 measured |
| Legal Research Bench (Vals AI) | Not measured | 41.4% | Only Hy4 measured |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 12.5% | Only Hy4 measured |
| Neither model has a result on the other 41 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Llama 3.3 Euryale 70B | Hy4 | Leader |
|---|---|---|---|
| HLE-Diamond (Artificial Analysis run) | Not measured | 32.7% | Only Hy4 measured |
| CritPt v2, hard subset (Artificial Analysis run) | Not measured | 39.0% | Only Hy4 measured |
| Neither model has a result on the other 24 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Llama 3.3 Euryale 70B | Hy4 | Leader |
|---|---|---|---|
| AA-Omniscience | Not measured | 5.4 | Only Hy4 measured |
| Neither model has a result on the other 20 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | Llama 3.3 Euryale 70B | Hy4 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1251 | Only Hy4 measured |
| Design Arena: UI components | Not measured | 1197 | Only Hy4 measured |
| Design Arena: game dev | Not measured | 1271 | Only Hy4 measured |
| Design Arena: 3D | Not measured | 1251 | Only Hy4 measured |
| Design Arena: all code categories | Not measured | 1254 | Only Hy4 measured |
| Neither model has a result on the other 4 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Llama 3.3 Euryale 70B | Hy4 | Leader |
|---|---|---|---|
| Vals Index | Not measured | 59.4% | Only Hy4 measured |
| Neither model has a result on the other 48 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 3.3 Euryale 70B costs less
Repository review
50K input + 3K output tokens
Hy4 costs less
Agent loop
200K input + 10K output tokens
Hy4 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 3.3 Euryale 70B | Tencent Hy4 |
|---|---|---|
| Maker | Sao10K | Tencent |
| Weights | Open weights | Open weights |
| Released | December 18, 2024 | November 4, 2026 |
| Context window | 131K | 1.05M |
| Input $/Mtok | $0.65 | $0.417 |
| Output $/Mtok | $0.75 | $1.2505 |
| Coding index | Not benchmarked | 65.2 |
| Independent measurements behind it | 0 | 2 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Llama 3.3 Euryale 70B better than Hy4 for coding?
Only Hy4 has a coding score, 65.2 on the Vibe Coding Index; Llama 3.3 Euryale 70B has none, so the two cannot be ranked on coding. Pick Llama 3.3 Euryale 70B for output tokens 1.7x cheaper ($0.75 vs $1.2505 per million).
Which is cheaper, Llama 3.3 Euryale 70B or Hy4?
Llama 3.3 Euryale 70B costs $0.65 per million input tokens and $0.75 per million output tokens; Hy4 costs $0.417 and $1.2505. Cost per solved task is known for neither of them.
Which has the bigger context window, Llama 3.3 Euryale 70B or Hy4?
Hy4, with 1.05M tokens against 131K.
Has any benchmark tested both Llama 3.3 Euryale 70B and Hy4?
No benchmark has tested both yet. Llama 3.3 Euryale 70B has none yet; Hy4 on Terminal-Bench 4 (Vals AI), Vibe Code Bench (Vals AI) and Terminal-Bench 4.0 (Artificial Analysis run). Compare them on price and context instead. Data as of November 14, 2026.