Llama 3.3 Euryale 70B vs Hy3
Hy3 costs 1.4x less per output token than Llama 3.3 Euryale 70B ($0.528 vs $0.75 per million). Updated November 14, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.75
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.528
Llama 3.3 Euryale 70B or Hy3: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
No benchmark has tested both yet. Llama 3.3 Euryale 70B has none yet; Hy3 on LMArena WebDev, SciCode 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
Neither has a coding score yet.
One side not measured
Web design
Design Arena: websites
No call
Only Hy3 has a Design Arena: websites result, 1221.
Directional only
Long documents
Listed context window
Hy3
Hy3 takes 262K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Hy3
Llama 3.3 Euryale 70B $0.0010, Hy3 $0.0004 per turn.
List prices
At a glance
- Coding index
- Llama 3.3 Euryale 70B not benchmarked, Hy3 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 3.3 Euryale 70B $0.75 against Hy3 $0.528 per million output tokens, 1.4x apart.
- Context window
- Llama 3.3 Euryale 70B takes 131K tokens, Hy3 262K.
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 Index8 boards measured
| Benchmark | Llama 3.3 Euryale 70B | Hy3 | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1505 | Only Hy3 measured |
| SciCode | Not measured | 48.6% | Only Hy3 measured |
| Terminal-Bench 4.0 (Artificial Analysis run) | Not measured | 0.5% | Only Hy3 measured |
| ALE-Bench | Not measured | 838.6 | Only Hy3 measured |
| LMArena Text: coding | Not measured | 1467 | Only Hy3 measured |
| LMArena Text: software and IT | Not measured | 1464 | Only Hy3 measured |
| LMArena WebDev: React | Not measured | 1506 | Only Hy3 measured |
| LMArena WebDev: HTML | Not measured | 1488 | Only Hy3 measured |
| Neither model has a result on the other 44 boards here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Llama 3.3 Euryale 70B | Hy3 | Leader |
|---|---|---|---|
| Toolathlon-Verified | Not measured | 56.8% | Only Hy3 measured |
| Neither model has a result on the other 43 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
| Benchmark | Llama 3.3 Euryale 70B | Hy3 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 89.7% | Only Hy3 measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 33.5% | Only Hy3 measured |
| HLE-Diamond (Artificial Analysis run) | Not measured | 11.6% | Only Hy3 measured |
| LMArena Text: hard prompts | Not measured | 1447 | Only Hy3 measured |
| LMArena Text: expert | Not measured | 1458 | Only Hy3 measured |
| LMArena Text: hard prompts in English | Not measured | 1453 | Only Hy3 measured |
| Neither model has a result on the other 20 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Llama 3.3 Euryale 70B | Hy3 | Leader |
|---|---|---|---|
| LMArena Text: math | Not measured | 1477 | Only Hy3 measured |
| LMArena Text: mathematical work | Not measured | 1480 | Only Hy3 measured |
| Neither model has a result on the other 12 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | Llama 3.3 Euryale 70B | Hy3 | Leader |
|---|---|---|---|
| LMArena Text: science | Not measured | 1455 | Only Hy3 measured |
| LMArena Text: medicine and healthcare | Not measured | 1449 | Only Hy3 measured |
| LMArena Text: legal and government | Not measured | 1425 | Only Hy3 measured |
| LMArena Text: business and finance | Not measured | 1425 | Only Hy3 measured |
| Neither model has a result on the other 17 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards measured
| Benchmark | Llama 3.3 Euryale 70B | Hy3 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1221 | Only Hy3 measured |
| Design Arena: UI components | Not measured | 1196 | Only Hy3 measured |
| Design Arena: game dev | Not measured | 1197 | Only Hy3 measured |
| Design Arena: data viz | Not measured | 1162 | Only Hy3 measured |
| Design Arena: 3D | Not measured | 1209 | Only Hy3 measured |
| Design Arena: all code categories | Not measured | 1215 | Only Hy3 measured |
| Design Arena: SVG | Not measured | 1191 | Only Hy3 measured |
| Design Arena: ASCII art | Not measured | 1155 | Only Hy3 measured |
| Neither model has a result on the other 1 board here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index19 boards measured
| Benchmark | Llama 3.3 Euryale 70B | Hy3 | Leader |
|---|---|---|---|
| Long context reasoning (AA-LCR) | Not measured | 79.0% | Only Hy3 measured |
| GDPval-AA | Not measured | 1069 | Only Hy3 measured |
| LMArena Text | Not measured | 1439 | Only Hy3 measured |
| LMArena Text: instruction following | Not measured | 1426 | Only Hy3 measured |
| LMArena Text: creative writing | Not measured | 1405 | Only Hy3 measured |
| LMArena Text: English | Not measured | 1447 | Only Hy3 measured |
| LMArena Text: non-English | Not measured | 1426 | Only Hy3 measured |
| LMArena Text: Chinese | Not measured | 1490 | Only Hy3 measured |
| LMArena Text: German | Not measured | 1436 | Only Hy3 measured |
| LMArena Text: Japanese | Not measured | 1395 | Only Hy3 measured |
| LMArena Text: Korean | Not measured | 1403 | Only Hy3 measured |
| LMArena Text: French | Not measured | 1444 | Only Hy3 measured |
| LMArena Text: Spanish | Not measured | 1454 | Only Hy3 measured |
| LMArena Text: Russian | Not measured | 1438 | Only Hy3 measured |
| LMArena Text: Polish | Not measured | 1446 | Only Hy3 measured |
| LMArena Text: multi-turn | Not measured | 1438 | Only Hy3 measured |
| LMArena Text: longer queries | Not measured | 1443 | Only Hy3 measured |
| LMArena Text: writing and language | Not measured | 1416 | Only Hy3 measured |
| LMArena Text: entertainment and media | Not measured | 1405 | Only Hy3 measured |
| Neither model has a result on the other 30 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
Hy3 costs less
Repository review
50K input + 3K output tokens
Hy3 costs less
Agent loop
200K input + 10K output tokens
Hy3 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 Hy3 |
|---|---|---|
| Maker | Sao10K | Tencent |
| Weights | Open weights | Open weights |
| Released | December 18, 2024 | July 6, 2026 |
| Context window | 131K | 262K |
| Input $/Mtok | $0.65 | $0.132 |
| Output $/Mtok | $0.75 | $0.528 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Llama 3.3 Euryale 70B better than Hy3 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, Llama 3.3 Euryale 70B or Hy3?
Llama 3.3 Euryale 70B costs $0.65 per million input tokens and $0.75 per million output tokens; Hy3 costs $0.132 and $0.528. Cost per solved task is known for neither of them.
Which has the bigger context window, Llama 3.3 Euryale 70B or Hy3?
Hy3, with 262K tokens against 131K.
Has any benchmark tested both Llama 3.3 Euryale 70B and Hy3?
No benchmark has tested both yet. Llama 3.3 Euryale 70B has none yet; Hy3 on LMArena WebDev, SciCode and Terminal-Bench 4.0 (Artificial Analysis run). Compare them on price and context instead. Data as of November 14, 2026.