Model comparison
Hy4 preview vs Llama 2-7B
Hy4 preview is the stronger model overall, scoring 45.3 to 29.1 on the Noometry Index.
Last verified . 0 shared benchmarks.
Tencent
MetaSummary
- The widest gap is in math, where Hy4 preview leads 55.7 to 30.7.
Side by side
| Hy4 preview | Llama 2-7B | |
|---|---|---|
| Provider | Tencent | Meta |
| Noometry Index | 45.3 | 29.1 |
| Released | 2026-08-28 | 2023-07-18 |
| Weights | Open | Open |
| Context window | 1.05M | — |
| Max output | 64K | — |
| Input $ / M tokens | $0.75 | — |
| Output $ / M tokens | $2.25 | — |
| Results tracked | 3 | 29 |
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Category by category
Coding Hy4 preview leads
Hy4 preview: 51.6 (#38), Llama 2-7B: 29.2 (#307)
| Benchmark | Hy4 preview | Llama 2-7B |
|---|---|---|
| LMArena WebDev | 1632 | — |
| LMArena Coding | — | 1002 |
Reasoning Hy4 preview leads
Hy4 preview: 31.9 (#79), Llama 2-7B: 15.7 (#312)
| Benchmark | Hy4 preview | Llama 2-7B |
|---|---|---|
| NYT Connections (extended) | 68.2% | — |
| Chess Puzzles | — | 0% |
| LMArena Hard Prompts | — | 1009 |
| BIG-Bench Hard | — | 39.2% |
| Epoch Capabilities Index | — | 99.06 |
| HellaSwag | — | 77.2% |
| LAMBADA | — | 73.3% |
| PIQA | — | 78.8% |
| WinoGrande | — | 69.2% |
Math Hy4 preview leads
Hy4 preview: 55.7 (#42), Llama 2-7B: 30.7 (#233)
| Benchmark | Hy4 preview | Llama 2-7B |
|---|---|---|
| ProofBench | 75% | — |
| LMArena Math | — | 1042 |
| GSM8K | — | 16.7% |
Knowledge Not comparable
Hy4 preview: —, Llama 2-7B: 28.2 (#248)
| Benchmark | Hy4 preview | Llama 2-7B |
|---|---|---|
| LMArena Expert | — | 1036 |
| ARC (AI2) Challenge | — | 45.9% |
| BoolQ | — | 77.9% |
| MMLU | — | 45.8% |
| OpenBookQA | — | 58.6% |
| TriviaQA | — | 73.7% |
Multimodal Not comparable
Hy4 preview: —, Llama 2-7B: —
| Benchmark | Hy4 preview | Llama 2-7B |
|---|---|---|
| ScienceQA | — | 43.1% |
Multilingual Not comparable
Hy4 preview: —, Llama 2-7B: 23.8 (#293)
| Benchmark | Hy4 preview | Llama 2-7B |
|---|---|---|
| LMArena Non-English | — | 973 |
| LMArena Chinese | — | 973 |
| LMArena French | — | 970 |
| LMArena German | — | 978 |
| LMArena Russian | — | 995 |
| LMArena Spanish | — | 1007 |
Instruction Following Not comparable
Hy4 preview: —, Llama 2-7B: 50.8 (#298)
| Benchmark | Hy4 preview | Llama 2-7B |
|---|---|---|
| LMArena Instruction Following | — | 1006 |
Long Context Not comparable
Hy4 preview: —, Llama 2-7B: 30.4 (#287)
| Benchmark | Hy4 preview | Llama 2-7B |
|---|---|---|
| LMArena Longer Query | — | 999 |
Writing & Preference Not comparable
Hy4 preview: —, Llama 2-7B: 28.0 (#298)
| Benchmark | Hy4 preview | Llama 2-7B |
|---|---|---|
| LMArena Text | — | 1053 |
| LMArena Creative Writing | — | 1033 |
| LMArena Multi-Turn | — | 1029 |
Frequently asked questions
Is Hy4 preview better than Llama 2-7B?
Hy4 preview is the stronger model overall, scoring 45.3 to 29.1 on the Noometry Index.
Is Hy4 preview or Llama 2-7B better for coding?
Hy4 preview scores higher on coding benchmarks: 51.6 versus 29.2 in the Noometry coding category.
How many benchmarks do Hy4 preview and Llama 2-7B share?
0 benchmarks have published results for both models. Hy4 preview has 3 scored results on Noometry and Llama 2-7B has 29.