Model comparison
Llama 3.1-70B vs Qwen3 Max
Qwen3 Max is the stronger model overall, scoring 43.5 to 29.4 on the Noometry Index. Llama 3.1-70B costs 6.0× less per token, which makes it the better buy when Qwen3 Max's lead doesn't matter for your workload.
Last verified . 23 shared benchmarks.
Meta
Alibaba (Qwen)Summary
- They share 23 benchmarks with published results for both. Llama 3.1-70B scores higher in 0 categories and Qwen3 Max in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Qwen3 Max leads 62.6 to 35.6.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 3.6% for Llama 3.1-70B and 73.3% for Qwen3 Max.
- Llama 3.1-70B is cheaper at $0.40 / $0.40 per million input/output tokens, against $1.20 / $6 for Qwen3 Max.
- Qwen3 Max accepts more context: 262K tokens versus 128K.
- Llama 3.1-70B has downloadable open weights; the other is API-only.
Side by side
| Llama 3.1-70B | Qwen3 Max | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 29.4 | 43.5 |
| Released | 2024-07-23 | 2025-09-23 |
| Weights | Open | Proprietary |
| Context window | 128K | 262K |
| Max output | 4K | 66K |
| Input $ / M tokens | $0.40 | $1.20 |
| Output $ / M tokens | $0.40 | $6 |
| Results tracked | 35 | 33 |
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Category by category
Coding Qwen3 Max leads
Llama 3.1-70B: 29.8 (#292), Qwen3 Max: 42.4 (#93)
| Benchmark | Llama 3.1-70B | Qwen3 Max |
|---|---|---|
| LMArena Coding | 1260 | 1456 |
| WeirdML | 9% | — |
| BigCodeBench Instruct | 46.1% | — |
| BigCodeBench Complete | 54.8% | — |
| ALE-Bench | — | 370.45 |
Agentic & Tool Use Not comparable
Llama 3.1-70B: 24.9 (#104), Qwen3 Max: —
| Benchmark | Llama 3.1-70B | Qwen3 Max |
|---|---|---|
| TheAgentCompany | 6.9% | — |
| BALROG | 27.9% | — |
| Vending-Bench 2 | — | 71.56 |
Reasoning Qwen3 Max leads
Llama 3.1-70B: 20.8 (#215), Qwen3 Max: 22.0 (#186)
| Benchmark | Llama 3.1-70B | Qwen3 Max |
|---|---|---|
| LMArena Hard Prompts | 1241 | 1448 |
| DTBench | 60% | 82.1% |
| LMCA | 14.8% | 28.3% |
| Epoch Capabilities Index | 125.91 | 142.41 |
| Kagi LLM Benchmark | — | 72.5% |
| NYT Connections (extended) | — | 30.1% |
| Chess Puzzles | — | 4% |
| Mystery Game Puzzles | — | 5% |
Math Qwen3 Max leads
Llama 3.1-70B: 12.7 (#298), Qwen3 Max: 37.6 (#94)
| Benchmark | Llama 3.1-70B | Qwen3 Max |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 3.6% | 73.3% |
| LMArena Math | 1252 | 1447 |
| MATH Level 5 | 36.7% | 97.1% |
| FrontierMath (Tiers 1-3) | — | 18.9% |
| Omni-MATH | 21% | — |
Knowledge Qwen3 Max leads
Llama 3.1-70B: 24.1 (#264), Qwen3 Max: 48.1 (#72)
| Benchmark | Llama 3.1-70B | Qwen3 Max |
|---|---|---|
| GPQA Diamond | 44.2% | 72.6% |
| LMArena Expert | 1209 | 1457 |
| SimpleQA Verified | — | 48.7% |
| MMLU-Pro | 65.3% | — |
| GPQA (HELM) | 42.6% | — |
| MMLU | 80.1% | — |
Multilingual Qwen3 Max leads
Llama 3.1-70B: 38.9 (#220), Qwen3 Max: 53.9 (#58)
| Benchmark | Llama 3.1-70B | Qwen3 Max |
|---|---|---|
| LMArena Non-English | 1219 | 1429 |
| LMArena Chinese | 1215 | 1479 |
| LMArena French | 1260 | 1450 |
| LMArena German | 1222 | 1463 |
| LMArena Japanese | 1132 | 1399 |
| LMArena Korean | 1140 | 1397 |
| LMArena Russian | 1234 | 1428 |
| LMArena Spanish | 1253 | 1463 |
Instruction Following Qwen3 Max leads
Llama 3.1-70B: 65.5 (#218), Qwen3 Max: 75.0 (#81)
| Benchmark | Llama 3.1-70B | Qwen3 Max |
|---|---|---|
| LMArena Instruction Following | 1231 | 1420 |
| IFEval | 82.1% | — |
Long Context Qwen3 Max leads
Llama 3.1-70B: 37.6 (#208), Qwen3 Max: 41.6 (#129)
| Benchmark | Llama 3.1-70B | Qwen3 Max |
|---|---|---|
| LMArena Longer Query | 1241 | 1439 |
| Fiction.LiveBench | — | 66.7% |
| CL-bench | — | 14.5% |
Writing & Preference Qwen3 Max leads
Llama 3.1-70B: 35.6 (#262), Qwen3 Max: 62.6 (#72)
| Benchmark | Llama 3.1-70B | Qwen3 Max |
|---|---|---|
| LMArena Text | 1261 | 1439 |
| LMArena Creative Writing | 1232 | 1401 |
| LMArena Multi-Turn | 1256 | 1446 |
| EQ-Bench Creative Writing | 784 | — |
| WildBench | 75.8% | — |
Frequently asked questions
Is Llama 3.1-70B better than Qwen3 Max?
Qwen3 Max is the stronger model overall, scoring 43.5 to 29.4 on the Noometry Index. Llama 3.1-70B costs 6.0× less per token, which makes it the better buy when Qwen3 Max's lead doesn't matter for your workload.
Which is cheaper, Llama 3.1-70B or Qwen3 Max?
Llama 3.1-70B is cheaper. It lists at $0.40 per million input tokens and $0.40 per million output tokens; Qwen3 Max lists at $1.20 and $6.
Is Llama 3.1-70B or Qwen3 Max better for coding?
Qwen3 Max scores higher on coding benchmarks: 42.4 versus 29.8 in the Noometry coding category.
Which has the bigger context window?
Qwen3 Max does, with 262K tokens against 128K.
How many benchmarks do Llama 3.1-70B and Qwen3 Max share?
23 benchmarks have published results for both models. Llama 3.1-70B has 35 scored results on Noometry and Qwen3 Max has 33.