Model comparison
Qwen3.8 Max vs Qwen3-Next 80B-A3B Instruct
Qwen3.8 Max is the stronger model overall, scoring 56.8 to 43.0 on the Noometry Index. Qwen3-Next 80B-A3B Instruct costs 3.4× less per token, which makes it the better buy when Qwen3.8 Max's lead doesn't matter for your workload.
Last verified . 17 shared benchmarks.
Alibaba (Qwen)Summary
- They share 17 benchmarks with published results for both. Qwen3.8 Max scores higher in 8 categories and Qwen3-Next 80B-A3B Instruct in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen3.8 Max leads 73.2 to 38.8.
- Qwen3-Next 80B-A3B Instruct is cheaper at $0.50 / $2 per million input/output tokens, against $2 / $6 for Qwen3.8 Max.
- Qwen3.8 Max accepts more context: 1M tokens versus 131K.
- Qwen3-Next 80B-A3B Instruct has downloadable open weights; the other is API-only.
Side by side
| Qwen3.8 Max | Qwen3-Next 80B-A3B Instruct | |
|---|---|---|
| Provider | Alibaba (Qwen) | Alibaba (Qwen) |
| Noometry Index | 56.8 | 43.0 |
| Released | 2026-08-02 | 2025-09 |
| Weights | Proprietary | Open |
| Context window | 1M | 131K |
| Max output | 131K | 33K |
| Input $ / M tokens | $2 | $0.50 |
| Output $ / M tokens | $6 | $2 |
| Results tracked | 39 | 25 |
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Category by category
Coding Qwen3.8 Max leads
Qwen3.8 Max: 53.5 (#29), Qwen3-Next 80B-A3B Instruct: 42.5 (#98)
| Benchmark | Qwen3.8 Max | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Coding | 1502 | 1440 |
| DeepSWE | 57.5% | — |
| LMArena WebDev | 1674 | — |
| FrontierSWE | 17.8% | — |
| SciCode | 53.2% | — |
Agentic & Tool Use Not comparable
Qwen3.8 Max: 45.4 (#14), Qwen3-Next 80B-A3B Instruct: —
| Benchmark | Qwen3.8 Max | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| APEX-Agents | 63.3% | — |
| τ²-bench Banking | 55.1% | — |
| GDP.pdf | 23.2% | — |
Reasoning Qwen3.8 Max leads
Qwen3.8 Max: 54.4 (#26), Qwen3-Next 80B-A3B Instruct: 31.1 (#81)
| Benchmark | Qwen3.8 Max | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Hard Prompts | 1496 | 1428 |
| Kagi LLM Benchmark | — | 66.7% |
| NYT Connections (extended) | 88.3% | — |
| CritPt | 20% | — |
| Chess Puzzles | 40% | — |
| Mystery Game Puzzles | 38% | — |
| DTBench | 92% | — |
| LMCA | 46.2% | — |
| Epoch Capabilities Index | 156.41 | — |
Math Qwen3.8 Max leads
Qwen3.8 Max: 73.2 (#20), Qwen3-Next 80B-A3B Instruct: 38.8 (#126)
| Benchmark | Qwen3.8 Max | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Math | 1499 | 1440 |
| FrontierMath (Tiers 1-3) | 74.7% | — |
| FrontierMath Tier 4 | 46.3% | — |
| OTIS Mock AIME 2024-2025 | 100% | — |
| ProofBench | 58% | — |
| Omni-MATH | — | 46.7% |
Knowledge Qwen3.8 Max leads
Qwen3.8 Max: 61.7 (#27), Qwen3-Next 80B-A3B Instruct: 41.8 (#106)
| Benchmark | Qwen3.8 Max | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Expert | 1507 | 1417 |
| GPQA Diamond | 92.7% | — |
| SimpleQA Verified | 47.3% | — |
| MMLU-Pro | — | 78.6% |
| Vectara Hallucination Rate | — | 9.3% |
| GPQA (HELM) | — | 63% |
Multimodal Not comparable
Qwen3.8 Max: 37.2 (#75), Qwen3-Next 80B-A3B Instruct: —
| Benchmark | Qwen3.8 Max | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Vision | 1314 | — |
| Furniture Assembly | 20% | — |
Multilingual Qwen3.8 Max leads
Qwen3.8 Max: 56.7 (#18), Qwen3-Next 80B-A3B Instruct: 52.1 (#93)
| Benchmark | Qwen3.8 Max | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Non-English | 1472 | 1407 |
| LMArena Chinese | 1538 | 1460 |
| LMArena French | 1503 | 1413 |
| LMArena German | 1483 | 1417 |
| LMArena Japanese | 1467 | 1395 |
| LMArena Korean | 1461 | 1364 |
| LMArena Russian | 1481 | 1404 |
| LMArena Spanish | 1492 | 1435 |
Instruction Following Qwen3.8 Max leads
Qwen3.8 Max: 77.6 (#17), Qwen3-Next 80B-A3B Instruct: 70.8 (#159)
| Benchmark | Qwen3.8 Max | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Instruction Following | 1479 | 1389 |
| IFEval | — | 81% |
Long Context Qwen3.8 Max leads
Qwen3.8 Max: 45.6 (#31), Qwen3-Next 80B-A3B Instruct: 37.0 (#223)
| Benchmark | Qwen3.8 Max | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Longer Query | 1489 | 1403 |
| Fiction.LiveBench | — | 55.6% |
Writing & Preference Qwen3.8 Max leads
Qwen3.8 Max: 67.1 (#30), Qwen3-Next 80B-A3B Instruct: 58.0 (#121)
| Benchmark | Qwen3.8 Max | Qwen3-Next 80B-A3B Instruct |
|---|---|---|
| LMArena Text | 1483 | 1417 |
| LMArena Creative Writing | 1479 | 1334 |
| LMArena Multi-Turn | 1489 | 1416 |
| WildBench | — | 80.7% |
Frequently asked questions
Is Qwen3.8 Max better than Qwen3-Next 80B-A3B Instruct?
Qwen3.8 Max is the stronger model overall, scoring 56.8 to 43.0 on the Noometry Index. Qwen3-Next 80B-A3B Instruct costs 3.4× less per token, which makes it the better buy when Qwen3.8 Max's lead doesn't matter for your workload.
Which is cheaper, Qwen3.8 Max or Qwen3-Next 80B-A3B Instruct?
Qwen3-Next 80B-A3B Instruct is cheaper. It lists at $0.50 per million input tokens and $2 per million output tokens; Qwen3.8 Max lists at $2 and $6.
Is Qwen3.8 Max or Qwen3-Next 80B-A3B Instruct better for coding?
Qwen3.8 Max scores higher on coding benchmarks: 53.5 versus 42.5 in the Noometry coding category.
Which has the bigger context window?
Qwen3.8 Max does, with 1M tokens against 131K.
How many benchmarks do Qwen3.8 Max and Qwen3-Next 80B-A3B Instruct share?
17 benchmarks have published results for both models. Qwen3.8 Max has 39 scored results on Noometry and Qwen3-Next 80B-A3B Instruct has 25.