Model comparison
Llama-3.3-70B-Instruct vs Qwen3-Next 80B-A3B Instruct
Qwen3-Next 80B-A3B Instruct is the stronger model overall, scoring 43.0 to 30.6 on the Noometry Index. Llama-3.3-70B-Instruct costs 5.6× less per token, which makes it the better buy when Qwen3-Next 80B-A3B Instruct's lead doesn't matter for your workload.
Last verified . 19 shared benchmarks.
Meta
Alibaba (Qwen)Summary
- They share 19 benchmarks with published results for both. Llama-3.3-70B-Instruct scores higher in 1 category and Qwen3-Next 80B-A3B Instruct in 7 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen3-Next 80B-A3B Instruct leads 38.8 to 15.3.
- The biggest single-benchmark swing is Fiction.LiveBench: 33.3% for Llama-3.3-70B-Instruct and 55.6% for Qwen3-Next 80B-A3B Instruct.
- Llama-3.3-70B-Instruct is cheaper at $0.10 / $0.32 per million input/output tokens, against $0.50 / $2 for Qwen3-Next 80B-A3B Instruct.
- Qwen3-Next 80B-A3B Instruct accepts more context: 131K tokens versus 128K.
Side by side
| Llama-3.3-70B-Instruct | Qwen3-Next 80B-A3B Instruct | |
|---|---|---|
| Provider | Meta | Alibaba (Qwen) |
| Noometry Index | 30.6 | 43.0 |
| Released | 2024-12-06 | 2025-09 |
| Weights | Open | Open |
| Context window | 128K | 131K |
| Max output | 4K | 33K |
| Input $ / M tokens | $0.10 | $0.50 |
| Output $ / M tokens | $0.32 | $2 |
| Results tracked | 43 | 25 |
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Category by category
Coding Qwen3-Next 80B-A3B Instruct leads
Llama-3.3-70B-Instruct: 31.0 (#290), Qwen3-Next 80B-A3B Instruct: 42.5 (#98)
| Benchmark | Llama-3.3-70B-Instruct | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Coding | 1268 | 1440 |
| SciCode | 26% | — |
| WeirdML | 14.4% | — |
| BigCodeBench Instruct | 46.9% | — |
| LiveBench Coding | 36.6% | — |
| BigCodeBench Complete | 57.5% | — |
Agentic & Tool Use Not comparable
Llama-3.3-70B-Instruct: 25.8 (#105), Qwen3-Next 80B-A3B Instruct: —
| Benchmark | Llama-3.3-70B-Instruct | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| Berkeley Function Calling Leaderboard | 31.9% | — |
| BALROG | 23% | — |
Reasoning Qwen3-Next 80B-A3B Instruct leads
Llama-3.3-70B-Instruct: 14.1 (#327), Qwen3-Next 80B-A3B Instruct: 31.1 (#81)
| Benchmark | Llama-3.3-70B-Instruct | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Hard Prompts | 1257 | 1428 |
| SimpleBench | 19.9% | — |
| Kagi LLM Benchmark | — | 66.7% |
| CritPt | 0% | — |
| LiveBench Reasoning | 50.8% | — |
| DTBench | 59.5% | — |
| LiveBench Data Analysis | 49.5% | — |
| LMCA | 17.5% | — |
| Epoch Capabilities Index | 127.33 | — |
| ForecastBench | 58.6 | — |
| LiveBench | 50.2% | — |
Math Qwen3-Next 80B-A3B Instruct leads
Llama-3.3-70B-Instruct: 15.3 (#298), Qwen3-Next 80B-A3B Instruct: 38.8 (#126)
| Benchmark | Llama-3.3-70B-Instruct | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Math | 1267 | 1440 |
| OTIS Mock AIME 2024-2025 | 5.1% | — |
| Omni-MATH | — | 46.7% |
| LiveBench Math | 42.2% | — |
| MATH Level 5 | 41.6% | — |
Knowledge Qwen3-Next 80B-A3B Instruct leads
Llama-3.3-70B-Instruct: 30.6 (#226), Qwen3-Next 80B-A3B Instruct: 41.8 (#106)
| Benchmark | Llama-3.3-70B-Instruct | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| Vectara Hallucination Rate | 4.1% | 9.3% |
| LMArena Expert | 1225 | 1417 |
| GPQA Diamond | 47.4% | — |
| MMLU-Pro | — | 78.6% |
| Confabulations | 22.8% | — |
| GPQA (HELM) | — | 63% |
| MMLU | 86.3% | — |
Multilingual Qwen3-Next 80B-A3B Instruct leads
Llama-3.3-70B-Instruct: 39.9 (#220), Qwen3-Next 80B-A3B Instruct: 52.1 (#93)
| Benchmark | Llama-3.3-70B-Instruct | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Non-English | 1236 | 1407 |
| LMArena Chinese | 1217 | 1460 |
| LMArena French | 1281 | 1413 |
| LMArena German | 1251 | 1417 |
| LMArena Japanese | 1150 | 1395 |
| LMArena Korean | 1143 | 1364 |
| LMArena Russian | 1252 | 1404 |
| LMArena Spanish | 1270 | 1435 |
Instruction Following Too close to call
Llama-3.3-70B-Instruct: 71.1 (#157), Qwen3-Next 80B-A3B Instruct: 70.8 (#159)
| Benchmark | Llama-3.3-70B-Instruct | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Instruction Following | 1242 | 1389 |
| LiveBench Instruction Following | 82.7% | — |
| IFEval | — | 81% |
Long Context Qwen3-Next 80B-A3B Instruct leads
Llama-3.3-70B-Instruct: 26.4 (#295), Qwen3-Next 80B-A3B Instruct: 37.0 (#223)
| Benchmark | Llama-3.3-70B-Instruct | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| Fiction.LiveBench | 33.3% | 55.6% |
| LMArena Longer Query | 1256 | 1403 |
Writing & Preference Qwen3-Next 80B-A3B Instruct leads
Llama-3.3-70B-Instruct: 47.6 (#207), Qwen3-Next 80B-A3B Instruct: 58.0 (#121)
| Benchmark | Llama-3.3-70B-Instruct | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Text | 1274 | 1417 |
| LMArena Creative Writing | 1250 | 1334 |
| LMArena Multi-Turn | 1280 | 1416 |
| WildBench | — | 80.7% |
| LiveBench Language | 39.2% | — |
Frequently asked questions
Is Llama-3.3-70B-Instruct better than Qwen3-Next 80B-A3B Instruct?
Qwen3-Next 80B-A3B Instruct is the stronger model overall, scoring 43.0 to 30.6 on the Noometry Index. Llama-3.3-70B-Instruct costs 5.6× less per token, which makes it the better buy when Qwen3-Next 80B-A3B Instruct's lead doesn't matter for your workload.
Which is cheaper, Llama-3.3-70B-Instruct or Qwen3-Next 80B-A3B Instruct?
Llama-3.3-70B-Instruct is cheaper. It lists at $0.10 per million input tokens and $0.32 per million output tokens; Qwen3-Next 80B-A3B Instruct lists at $0.50 and $2.
Is Llama-3.3-70B-Instruct or Qwen3-Next 80B-A3B Instruct better for coding?
Qwen3-Next 80B-A3B Instruct scores higher on coding benchmarks: 42.5 versus 31.0 in the Noometry coding category.
Which has the bigger context window?
Qwen3-Next 80B-A3B Instruct does, with 131K tokens against 128K.
How many benchmarks do Llama-3.3-70B-Instruct and Qwen3-Next 80B-A3B Instruct share?
19 benchmarks have published results for both models. Llama-3.3-70B-Instruct has 43 scored results on Noometry and Qwen3-Next 80B-A3B Instruct has 25.