Model comparison
Hy4 preview vs Llama 3.1-8B
Hy4 preview is the stronger model overall, scoring 45.3 to 23.0 on the Noometry Index. Llama 3.1-8B costs 20× 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 10.2.
- Llama 3.1-8B is cheaper at $0.05 / $0.08 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 3.1-8B | |
|---|---|---|
| Provider | Tencent | Meta |
| Noometry Index | 45.3 | 23.0 |
| Released | 2026-08-28 | 2024-07-23 |
| Weights | Open | Open |
| Context window | 1.05M | 128K |
| Max output | 64K | 4K |
| Input $ / M tokens | $0.75 | $0.05 |
| Output $ / M tokens | $2.25 | $0.08 |
| Results tracked | 3 | 43 |
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Category by category
Coding Hy4 preview leads
Hy4 preview: 51.6 (#38), Llama 3.1-8B: 20.2 (#340)
| Benchmark | Hy4 preview | Llama 3.1-8B |
|---|---|---|
| LMArena WebDev | 1632 | — |
| SciCode | — | 13.2% |
| WeirdML | — | 1.7% |
| BigCodeBench Instruct | — | 32.8% |
| LMArena Coding | — | 1195 |
| BigCodeBench Complete | — | 40.5% |
| HumanEval+ | — | 62.8% |
| MBPP+ | — | 55.6% |
Agentic & Tool Use Not comparable
Hy4 preview: —, Llama 3.1-8B: 22.5 (#131)
| Benchmark | Hy4 preview | Llama 3.1-8B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 25.8% |
| BALROG | — | 15.1% |
Reasoning Hy4 preview leads
Hy4 preview: 31.9 (#79), Llama 3.1-8B: 14.9 (#321)
| Benchmark | Hy4 preview | Llama 3.1-8B |
|---|---|---|
| NYT Connections (extended) | 68.2% | — |
| CritPt | — | 0% |
| Chess Puzzles | — | 0% |
| LMArena Hard Prompts | — | 1175 |
| DTBench | — | 50.9% |
| LMCA | — | 5.4% |
| Epoch Capabilities Index | — | 116.57 |
| PIQA | — | 81.2% |
Math Hy4 preview leads
Hy4 preview: 55.7 (#42), Llama 3.1-8B: 10.2 (#317)
| Benchmark | Hy4 preview | Llama 3.1-8B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 1.7% |
| ProofBench | 75% | — |
| Omni-MATH | — | 13.7% |
| LMArena Math | — | 1179 |
| MATH Level 5 | — | 22.9% |
| GSM8K | — | 82.4% |
Knowledge Not comparable
Hy4 preview: —, Llama 3.1-8B: 8.0 (#307)
| Benchmark | Hy4 preview | Llama 3.1-8B |
|---|---|---|
| GPQA Diamond | — | 27% |
| MMLU-Pro | — | 40.6% |
| GPQA (HELM) | — | 24.7% |
| LMArena Expert | — | 1144 |
| BoolQ | — | 82.8% |
| MMLU | — | 56.1% |
Multilingual Not comparable
Hy4 preview: —, Llama 3.1-8B: 34.0 (#249)
| Benchmark | Hy4 preview | Llama 3.1-8B |
|---|---|---|
| LMArena Non-English | — | 1148 |
| LMArena Chinese | — | 1151 |
| LMArena French | — | 1177 |
| LMArena German | — | 1144 |
| LMArena Japanese | — | 1061 |
| LMArena Korean | — | 1053 |
| LMArena Russian | — | 1158 |
| LMArena Spanish | — | 1169 |
Instruction Following Not comparable
Hy4 preview: —, Llama 3.1-8B: 58.9 (#258)
| Benchmark | Hy4 preview | Llama 3.1-8B |
|---|---|---|
| IFEval | — | 74.3% |
| LMArena Instruction Following | — | 1159 |
Long Context Not comparable
Hy4 preview: —, Llama 3.1-8B: 35.8 (#238)
| Benchmark | Hy4 preview | Llama 3.1-8B |
|---|---|---|
| LMArena Longer Query | — | 1182 |
Writing & Preference Not comparable
Hy4 preview: —, Llama 3.1-8B: 29.7 (#290)
| Benchmark | Hy4 preview | Llama 3.1-8B |
|---|---|---|
| LMArena Text | — | 1187 |
| LMArena Creative Writing | — | 1154 |
| EQ-Bench Creative Writing | — | 713 |
| WildBench | — | 68.7% |
| LMArena Multi-Turn | — | 1172 |
Frequently asked questions
Is Hy4 preview better than Llama 3.1-8B?
Hy4 preview is the stronger model overall, scoring 45.3 to 23.0 on the Noometry Index. Llama 3.1-8B costs 20× 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 3.1-8B?
Llama 3.1-8B is cheaper. It lists at $0.05 per million input tokens and $0.08 per million output tokens; Hy4 preview lists at $0.75 and $2.25.
Is Hy4 preview or Llama 3.1-8B better for coding?
Hy4 preview scores higher on coding benchmarks: 51.6 versus 20.2 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 3.1-8B share?
0 benchmarks have published results for both models. Hy4 preview has 3 scored results on Noometry and Llama 3.1-8B has 43.