Model comparison
Hy4 preview vs Llama 3.1-70B
Hy4 preview is the stronger model overall, scoring 45.3 to 29.6 on the Noometry Index. Llama 3.1-70B costs 2.8× less per token, which makes it the better buy when Hy4 preview's lead doesn't matter for your workload.
Last verified . 0 shared benchmarks.
Tencent
MetaSummary
- The widest gap is in math, where Hy4 preview leads 55.7 to 13.5.
- Llama 3.1-70B is cheaper at $0.40 / $0.40 per million input/output tokens, against $0.75 / $2.25 for Hy4 preview.
- Hy4 preview accepts more context: 1.05M tokens versus 128K.
Side by side
| Hy4 preview | Llama 3.1-70B | |
|---|---|---|
| Provider | Tencent | Meta |
| Noometry Index | 45.3 | 29.6 |
| Released | 2026-08-28 | 2024-07-23 |
| Weights | Open | Open |
| Context window | 1.05M | 128K |
| Max output | 64K | 4K |
| Input $ / M tokens | $0.75 | $0.40 |
| Output $ / M tokens | $2.25 | $0.40 |
| Results tracked | 3 | 35 |
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Category by category
Coding Hy4 preview leads
Hy4 preview: 51.6 (#38), Llama 3.1-70B: 30.3 (#296)
| Benchmark | Hy4 preview | Llama 3.1-70B |
|---|---|---|
| LMArena WebDev | 1632 | — |
| WeirdML | — | 9% |
| BigCodeBench Instruct | — | 46.1% |
| LMArena Coding | — | 1260 |
| BigCodeBench Complete | — | 54.8% |
Agentic & Tool Use Not comparable
Hy4 preview: —, Llama 3.1-70B: 25.1 (#112)
| Benchmark | Hy4 preview | Llama 3.1-70B |
|---|---|---|
| TheAgentCompany | — | 6.9% |
| BALROG | — | 27.9% |
Reasoning Hy4 preview leads
Hy4 preview: 31.9 (#79), Llama 3.1-70B: 21.6 (#220)
| Benchmark | Hy4 preview | Llama 3.1-70B |
|---|---|---|
| NYT Connections (extended) | 68.2% | — |
| LMArena Hard Prompts | — | 1241 |
| DTBench | — | 60% |
| LMCA | — | 14.8% |
| Epoch Capabilities Index | — | 125.92 |
Math Hy4 preview leads
Hy4 preview: 55.7 (#42), Llama 3.1-70B: 13.5 (#304)
| Benchmark | Hy4 preview | Llama 3.1-70B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 3.6% |
| ProofBench | 75% | — |
| Omni-MATH | — | 21% |
| LMArena Math | — | 1252 |
| MATH Level 5 | — | 36.7% |
Knowledge Not comparable
Hy4 preview: —, Llama 3.1-70B: 24.2 (#269)
| Benchmark | Hy4 preview | Llama 3.1-70B |
|---|---|---|
| GPQA Diamond | — | 44.2% |
| MMLU-Pro | — | 65.3% |
| GPQA (HELM) | — | 42.6% |
| LMArena Expert | — | 1209 |
| MMLU | — | 80.1% |
Multilingual Not comparable
Hy4 preview: —, Llama 3.1-70B: 38.8 (#225)
| Benchmark | Hy4 preview | Llama 3.1-70B |
|---|---|---|
| LMArena Non-English | — | 1219 |
| LMArena Chinese | — | 1215 |
| LMArena French | — | 1261 |
| LMArena German | — | 1222 |
| LMArena Japanese | — | 1132 |
| LMArena Korean | — | 1140 |
| LMArena Russian | — | 1234 |
| LMArena Spanish | — | 1253 |
Instruction Following Not comparable
Hy4 preview: —, Llama 3.1-70B: 65.3 (#223)
| Benchmark | Hy4 preview | Llama 3.1-70B |
|---|---|---|
| IFEval | — | 82.1% |
| LMArena Instruction Following | — | 1231 |
Long Context Not comparable
Hy4 preview: —, Llama 3.1-70B: 37.6 (#214)
| Benchmark | Hy4 preview | Llama 3.1-70B |
|---|---|---|
| LMArena Longer Query | — | 1241 |
Writing & Preference Not comparable
Hy4 preview: —, Llama 3.1-70B: 35.4 (#267)
| Benchmark | Hy4 preview | Llama 3.1-70B |
|---|---|---|
| LMArena Text | — | 1261 |
| LMArena Creative Writing | — | 1232 |
| EQ-Bench Creative Writing | — | 784 |
| WildBench | — | 75.8% |
| LMArena Multi-Turn | — | 1256 |
Frequently asked questions
Is Hy4 preview better than Llama 3.1-70B?
Hy4 preview is the stronger model overall, scoring 45.3 to 29.6 on the Noometry Index. Llama 3.1-70B costs 2.8× less per token, which makes it the better buy when Hy4 preview's lead doesn't matter for your workload.
Which is cheaper, Hy4 preview or Llama 3.1-70B?
Llama 3.1-70B is cheaper. It lists at $0.40 per million input tokens and $0.40 per million output tokens; Hy4 preview lists at $0.75 and $2.25.
Is Hy4 preview or Llama 3.1-70B better for coding?
Hy4 preview scores higher on coding benchmarks: 51.6 versus 30.3 in the Noometry coding category.
Which has the bigger context window?
Hy4 preview does, with 1.05M tokens against 128K.
How many benchmarks do Hy4 preview and Llama 3.1-70B share?
0 benchmarks have published results for both models. Hy4 preview has 3 scored results on Noometry and Llama 3.1-70B has 35.