Model comparison
Llama 3.1-70B vs Qwen2.5-VL 72B Instruct
Llama 3.1-70B and Qwen2.5-VL 72B Instruct score almost the same on the Noometry Index (29.6 vs 29.9), so choose on price, context window or the category you care about most.
Last verified . 0 shared benchmarks.
Meta
Alibaba (Qwen)Summary
- The widest gap is in agentic & tool use, where Llama 3.1-70B leads 25.1 to 18.6.
- Llama 3.1-70B is cheaper at $0.40 / $0.40 per million input/output tokens, against $2.80 / $8.40 for Qwen2.5-VL 72B Instruct.
- Qwen2.5-VL 72B Instruct accepts more context: 131K tokens versus 128K.
Side by side
| Llama 3.1-70B | Qwen2.5-VL 72B Instruct | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 29.6 | 29.9 |
| Released | 2024-07-23 | 2024-09 |
| Weights | Open | Open |
| Context window | 128K | 131K |
| Max output | 4K | 8K |
| Input $ / M tokens | $0.40 | $2.80 |
| Output $ / M tokens | $0.40 | $8.40 |
| Results tracked | 35 | 6 |
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Category by category
Coding Not comparable
Llama 3.1-70B: 30.3 (#296), Qwen2.5-VL 72B Instruct: —
| Benchmark | Llama 3.1-70B | Qwen2.5-VL 72B Instruct |
|---|---|---|
| WeirdML | 9% | — |
| BigCodeBench Instruct | 46.1% | — |
| LMArena Coding | 1260 | — |
| BigCodeBench Complete | 54.8% | — |
Agentic & Tool Use Llama 3.1-70B leads
Llama 3.1-70B: 25.1 (#112), Qwen2.5-VL 72B Instruct: 18.6 (#144)
| Benchmark | Llama 3.1-70B | Qwen2.5-VL 72B Instruct |
|---|---|---|
| TheAgentCompany | 6.9% | — |
| OSWorld | — | 5% |
| BALROG | 27.9% | — |
Reasoning Too close to call
Llama 3.1-70B: 21.6 (#220), Qwen2.5-VL 72B Instruct: 20.7 (#233)
| Benchmark | Llama 3.1-70B | Qwen2.5-VL 72B Instruct |
|---|---|---|
| Kagi LLM Benchmark | — | 36% |
| LMArena Hard Prompts | 1241 | — |
| DTBench | 60% | — |
| LMCA | 14.8% | — |
| Epoch Capabilities Index | 125.92 | — |
Math Not comparable
Llama 3.1-70B: 13.5 (#304), Qwen2.5-VL 72B Instruct: —
| Benchmark | Llama 3.1-70B | Qwen2.5-VL 72B Instruct |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 3.6% | — |
| Omni-MATH | 21% | — |
| LMArena Math | 1252 | — |
| MATH Level 5 | 36.7% | — |
Knowledge Not comparable
Llama 3.1-70B: 24.2 (#269), Qwen2.5-VL 72B Instruct: —
| Benchmark | Llama 3.1-70B | Qwen2.5-VL 72B Instruct |
|---|---|---|
| GPQA Diamond | 44.2% | — |
| MMLU-Pro | 65.3% | — |
| GPQA (HELM) | 42.6% | — |
| LMArena Expert | 1209 | — |
| MMLU | 80.1% | — |
Multimodal Not comparable
Llama 3.1-70B: —, Qwen2.5-VL 72B Instruct: 33.5 (#97)
| Benchmark | Llama 3.1-70B | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Vision | — | 1107 |
| Video-MME | — | 73.5% |
| GeoBench | — | 62% |
| SpatialViz-Bench | — | 33.3% |
Multilingual Not comparable
Llama 3.1-70B: 38.8 (#225), Qwen2.5-VL 72B Instruct: —
| Benchmark | Llama 3.1-70B | Qwen2.5-VL 72B Instruct |
|---|---|---|
| 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
Llama 3.1-70B: 65.3 (#223), Qwen2.5-VL 72B Instruct: —
| Benchmark | Llama 3.1-70B | Qwen2.5-VL 72B Instruct |
|---|---|---|
| IFEval | 82.1% | — |
| LMArena Instruction Following | 1231 | — |
Long Context Not comparable
Llama 3.1-70B: 37.6 (#214), Qwen2.5-VL 72B Instruct: —
| Benchmark | Llama 3.1-70B | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Longer Query | 1241 | — |
Writing & Preference Not comparable
Llama 3.1-70B: 35.4 (#267), Qwen2.5-VL 72B Instruct: —
| Benchmark | Llama 3.1-70B | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Text | 1261 | — |
| LMArena Creative Writing | 1232 | — |
| EQ-Bench Creative Writing | 784 | — |
| WildBench | 75.8% | — |
| LMArena Multi-Turn | 1256 | — |
Frequently asked questions
Is Llama 3.1-70B better than Qwen2.5-VL 72B Instruct?
Llama 3.1-70B and Qwen2.5-VL 72B Instruct score almost the same on the Noometry Index (29.6 vs 29.9), so choose on price, context window or the category you care about most.
Which is cheaper, Llama 3.1-70B or Qwen2.5-VL 72B Instruct?
Llama 3.1-70B is cheaper. It lists at $0.40 per million input tokens and $0.40 per million output tokens; Qwen2.5-VL 72B Instruct lists at $2.80 and $8.40.
Which has the bigger context window?
Qwen2.5-VL 72B Instruct does, with 131K tokens against 128K.
How many benchmarks do Llama 3.1-70B and Qwen2.5-VL 72B Instruct share?
0 benchmarks have published results for both models. Llama 3.1-70B has 35 scored results on Noometry and Qwen2.5-VL 72B Instruct has 6.