Model comparison
Llama 3.1-70B vs Qwen3.6 Plus
Qwen3.6 Plus is the stronger model overall, scoring 47.3 to 29.4 on the Noometry Index. Llama 3.1-70B costs 2.8× less per token, which makes it the better buy when Qwen3.6 Plus's lead doesn't matter for your workload.
Last verified . 22 shared benchmarks.
Meta
Alibaba (Qwen)Summary
- They share 22 benchmarks with published results for both. Llama 3.1-70B scores higher in 0 categories and Qwen3.6 Plus in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen3.6 Plus leads 50.6 to 12.7.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 3.6% for Llama 3.1-70B and 93.3% for Qwen3.6 Plus.
- Llama 3.1-70B is cheaper at $0.40 / $0.40 per million input/output tokens, against $0.50 / $3 for Qwen3.6 Plus.
- Qwen3.6 Plus accepts more context: 1M tokens versus 128K.
- Llama 3.1-70B has downloadable open weights; the other is API-only.
Side by side
| Llama 3.1-70B | Qwen3.6 Plus | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 29.4 | 47.3 |
| Released | 2024-07-23 | 2026-03-31 |
| Weights | Open | Proprietary |
| Context window | 128K | 1M |
| Max output | 4K | 66K |
| Input $ / M tokens | $0.40 | $0.50 |
| Output $ / M tokens | $0.40 | $3 |
| Results tracked | 35 | 37 |
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Category by category
Coding Qwen3.6 Plus leads
Llama 3.1-70B: 29.8 (#292), Qwen3.6 Plus: 40.6 (#125)
| Benchmark | Llama 3.1-70B | Qwen3.6 Plus |
|---|---|---|
| LMArena Coding | 1260 | 1467 |
| SWE-bench Verified | — | 57.9% |
| LMArena WebDev | — | 1461 |
| SciCode | — | 40.7% |
| WeirdML | 9% | — |
| BigCodeBench Instruct | 46.1% | — |
| BigCodeBench Complete | 54.8% | — |
| ALE-Bench | — | 670.15 |
Agentic & Tool Use Not comparable
Llama 3.1-70B: 24.9 (#104), Qwen3.6 Plus: —
| Benchmark | Llama 3.1-70B | Qwen3.6 Plus |
|---|---|---|
| TheAgentCompany | 6.9% | — |
| BALROG | 27.9% | — |
| Vending-Bench 2 | — | 5,115 |
Reasoning Qwen3.6 Plus leads
Llama 3.1-70B: 20.8 (#215), Qwen3.6 Plus: 28.5 (#89)
| Benchmark | Llama 3.1-70B | Qwen3.6 Plus |
|---|---|---|
| LMArena Hard Prompts | 1241 | 1449 |
| DTBench | 60% | 81.9% |
| LMCA | 14.8% | 33.1% |
| Epoch Capabilities Index | 125.91 | 147.67 |
| NYT Connections (extended) | — | 60.3% |
| CritPt | — | 2.9% |
| Chess Puzzles | — | 17% |
| Thematic Generalization | — | 59.5% |
| Mystery Game Puzzles | — | 12% |
Math Qwen3.6 Plus leads
Llama 3.1-70B: 12.7 (#298), Qwen3.6 Plus: 50.6 (#44)
| Benchmark | Llama 3.1-70B | Qwen3.6 Plus |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 3.6% | 93.3% |
| LMArena Math | 1252 | 1450 |
| FrontierMath (Tiers 1-3) | — | 38.2% |
| Omni-MATH | 21% | — |
| MATH Level 5 | 36.7% | — |
| FrontierMath (Feb 2025 set) | — | 26.2% |
| FrontierMath Tier 4 (v1) | — | 8.3% |
Knowledge Qwen3.6 Plus leads
Llama 3.1-70B: 24.1 (#264), Qwen3.6 Plus: 56.1 (#40)
| Benchmark | Llama 3.1-70B | Qwen3.6 Plus |
|---|---|---|
| GPQA Diamond | 44.2% | 88.4% |
| LMArena Expert | 1209 | 1456 |
| SimpleQA Verified | — | 44.1% |
| MMLU-Pro | 65.3% | — |
| GPQA (HELM) | 42.6% | — |
| MMLU | 80.1% | — |
Multilingual Qwen3.6 Plus leads
Llama 3.1-70B: 38.9 (#220), Qwen3.6 Plus: 53.5 (#66)
| Benchmark | Llama 3.1-70B | Qwen3.6 Plus |
|---|---|---|
| LMArena Non-English | 1219 | 1424 |
| LMArena Chinese | 1215 | 1478 |
| LMArena French | 1260 | 1454 |
| LMArena German | 1222 | 1451 |
| LMArena Japanese | 1132 | 1389 |
| LMArena Korean | 1140 | 1381 |
| LMArena Russian | 1234 | 1434 |
| LMArena Spanish | 1253 | 1432 |
Instruction Following Qwen3.6 Plus leads
Llama 3.1-70B: 65.5 (#218), Qwen3.6 Plus: 75.2 (#70)
| Benchmark | Llama 3.1-70B | Qwen3.6 Plus |
|---|---|---|
| LMArena Instruction Following | 1231 | 1425 |
| IFEval | 82.1% | — |
Long Context Qwen3.6 Plus leads
Llama 3.1-70B: 37.6 (#208), Qwen3.6 Plus: 45.1 (#48)
| Benchmark | Llama 3.1-70B | Qwen3.6 Plus |
|---|---|---|
| LMArena Longer Query | 1241 | 1440 |
| CL-bench | — | 20.3% |
Writing & Preference Qwen3.6 Plus leads
Llama 3.1-70B: 35.6 (#262), Qwen3.6 Plus: 62.4 (#78)
| Benchmark | Llama 3.1-70B | Qwen3.6 Plus |
|---|---|---|
| LMArena Text | 1261 | 1437 |
| LMArena Creative Writing | 1232 | 1405 |
| LMArena Multi-Turn | 1256 | 1438 |
| EQ-Bench Creative Writing | 784 | — |
| WildBench | 75.8% | — |
Frequently asked questions
Is Llama 3.1-70B better than Qwen3.6 Plus?
Qwen3.6 Plus is the stronger model overall, scoring 47.3 to 29.4 on the Noometry Index. Llama 3.1-70B costs 2.8× less per token, which makes it the better buy when Qwen3.6 Plus's lead doesn't matter for your workload.
Which is cheaper, Llama 3.1-70B or Qwen3.6 Plus?
Llama 3.1-70B is cheaper. It lists at $0.40 per million input tokens and $0.40 per million output tokens; Qwen3.6 Plus lists at $0.50 and $3.
Is Llama 3.1-70B or Qwen3.6 Plus better for coding?
Qwen3.6 Plus scores higher on coding benchmarks: 40.6 versus 29.8 in the Noometry coding category.
Which has the bigger context window?
Qwen3.6 Plus does, with 1M tokens against 128K.
How many benchmarks do Llama 3.1-70B and Qwen3.6 Plus share?
22 benchmarks have published results for both models. Llama 3.1-70B has 35 scored results on Noometry and Qwen3.6 Plus has 37.