MiniMax M2.1 vs Qwen3.8 Flash
Qwen3.8 Flash costs 2.6x less per output token than MiniMax M2.1 ($0.47 vs $1.20 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $1.20
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.47
MiniMax M2.1 or Qwen3.8 Flash: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
No benchmark has tested both yet. MiniMax M2.1 has results on LiveCodeBench (Vals AI), SWE-bench Verified (Vals AI) and LiveCodeBench (Artificial Analysis run); Qwen3.8 Flash on LiveBench coding, LiveBench research and LiveBench browser. Compare them on price and context instead.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
No call
Only MiniMax M2.1 has a AA Intelligence Index result, 20.9.
Directional only
Reasoning
GPQA Diamond
No call
Only MiniMax M2.1 has a GPQA Diamond result, 78.5%.
Directional only
Math
AIME
No call
Only MiniMax M2.1 has a AIME result, 77.9%.
Directional only
Knowledge
MMLU Pro
No call
Only MiniMax M2.1 has a MMLU Pro result, 87.0%.
Directional only
Web design
Design Arena: websites
No call
Only MiniMax M2.1 has a Design Arena: websites result, 1201.
Directional only
Long documents
Listed context window
Qwen3.8 Flash
Qwen3.8 Flash takes 1M tokens against 205K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.8 Flash
MiniMax M2.1 $0.0009, Qwen3.8 Flash $0.0004 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only MiniMax M2.1 has the number, $0.59.
Directional only
At a glance
- Coding index
- MiniMax M2.1 not benchmarked, Qwen3.8 Flash not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- MiniMax M2.1 $1.20 against Qwen3.8 Flash $0.47 per million output tokens, 2.6x apart.
- Context window
- MiniMax M2.1 takes 205K tokens, Qwen3.8 Flash 1M.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index7 boards measured
| Benchmark | MiniMax M2.1 | Qwen3.8 Flash | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 87.4% | Only Qwen3.8 Flash measured |
| LiveCodeBench (Vals AI) | 81.8% | Not measured | Only MiniMax M2.1 measured |
| SWE-bench Verified (Vals AI) | 74.8% | Not measured | Only MiniMax M2.1 measured |
| LiveCodeBench (Artificial Analysis run) | 81.0% | Not measured | Only MiniMax M2.1 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 28.8% | Not measured | Only MiniMax M2.1 measured |
| Terminal-Bench | 36.6% | Not measured | Only MiniMax M2.1 measured |
| ALE-Bench | 623.8 | Not measured | Only MiniMax M2.1 measured |
| Neither model has a result on the other 36 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | MiniMax M2.1 | Qwen3.8 Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 20.9 | Not measured | Only MiniMax M2.1 measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | MiniMax M2.1 | Qwen3.8 Flash | Leader |
|---|---|---|---|
| LiveBench research | Not measured | 74.6% | Only Qwen3.8 Flash measured |
| LiveBench browser | Not measured | 48.0% | Only Qwen3.8 Flash measured |
| LiveBench long agentic | Not measured | 37.1% | Only Qwen3.8 Flash measured |
| τ²-Bench Telecom | 85.4% | Not measured | Only MiniMax M2.1 measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | MiniMax M2.1 | Qwen3.8 Flash | Leader |
|---|---|---|---|
| GPQA Diamond | 78.5% | Not measured | Only MiniMax M2.1 measured |
| LiveBench reasoning | Not measured | 87.4% | Only Qwen3.8 Flash measured |
| GPQA Diamond (Artificial Analysis run) | 83.0% | Not measured | Only MiniMax M2.1 measured |
| Humanity's Last Exam (Artificial Analysis run) | 23.2% | Not measured | Only MiniMax M2.1 measured |
| Neither model has a result on the other 19 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | MiniMax M2.1 | Qwen3.8 Flash | Leader |
|---|---|---|---|
| AIME | 77.9% | Not measured | Only MiniMax M2.1 measured |
| MATH 500 (Vals AI) | 89.0% | Not measured | Only MiniMax M2.1 measured |
| MGSM (Vals AI) | 87.8% | Not measured | Only MiniMax M2.1 measured |
| AA Math Index | 82.7 | Not measured | Only MiniMax M2.1 measured |
| AIME 2025 (Artificial Analysis run) | 82.7% | Not measured | Only MiniMax M2.1 measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index8 boards measured
| Benchmark | MiniMax M2.1 | Qwen3.8 Flash | Leader |
|---|---|---|---|
| MMLU Pro | 87.0% | Not measured | Only MiniMax M2.1 measured |
| LegalBench (Vals AI) | 75.5% | Not measured | Only MiniMax M2.1 measured |
| CaseLaw (Vals AI) | 55.8% | Not measured | Only MiniMax M2.1 measured |
| CorpFin (Vals AI) | 58.9% | Not measured | Only MiniMax M2.1 measured |
| TaxEval (Vals AI) | 66.3% | Not measured | Only MiniMax M2.1 measured |
| MedQA (Vals AI) | 91.2% | Not measured | Only MiniMax M2.1 measured |
| MedCode (Vals AI) | 34.1% | Not measured | Only MiniMax M2.1 measured |
| MMLU Pro (Artificial Analysis run) | 87.5% | Not measured | Only MiniMax M2.1 measured |
| Neither model has a result on the other 12 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards measured
| Benchmark | MiniMax M2.1 | Qwen3.8 Flash | Leader |
|---|---|---|---|
| Design Arena: websites | 1201 | Not measured | Only MiniMax M2.1 measured |
| Design Arena: UI components | 1220 | Not measured | Only MiniMax M2.1 measured |
| Design Arena: game dev | 1134 | Not measured | Only MiniMax M2.1 measured |
| Design Arena: data viz | 1206 | Not measured | Only MiniMax M2.1 measured |
| Design Arena: 3D | 1164 | Not measured | Only MiniMax M2.1 measured |
| Design Arena: all code categories | 1190 | Not measured | Only MiniMax M2.1 measured |
| Design Arena: SVG | 1131 | Not measured | Only MiniMax M2.1 measured |
| LiveBench design | Not measured | 72.8% | Only Qwen3.8 Flash measured |
| Neither model has a result on the other 1 board here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | MiniMax M2.1 | Qwen3.8 Flash | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 74.2% | Only Qwen3.8 Flash measured |
| MedScribe (Vals AI) | 80.8% | Not measured | Only MiniMax M2.1 measured |
| IFBench | 69.9% | Not measured | Only MiniMax M2.1 measured |
| Long context reasoning (AA-LCR) | 67.7% | Not measured | Only MiniMax M2.1 measured |
| Neither model has a result on the other 44 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Qwen3.8 Flash costs less
Repository review
50K input + 3K output tokens
Qwen3.8 Flash costs less
Agent loop
200K input + 10K output tokens
Qwen3.8 Flash costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | MiniMax M2.1 | Qwen3.8 Flash |
|---|---|---|
| Maker | MiniMax | Qwen |
| Weights | Open weights | Open weights |
| Released | December 23, 2025 | August 26, 2026 |
| Context window | 205K | 1M |
| Input $/Mtok | $0.30 | $0.15 |
| Output $/Mtok | $1.20 | $0.47 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | $0.59 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is MiniMax M2.1 better than Qwen3.8 Flash for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, MiniMax M2.1 or Qwen3.8 Flash?
MiniMax M2.1 costs $0.30 per million input tokens and $1.20 per million output tokens; Qwen3.8 Flash costs $0.15 and $0.47. Cost per solved task is known for MiniMax M2.1 only.
Which has the bigger context window, MiniMax M2.1 or Qwen3.8 Flash?
Qwen3.8 Flash, with 1M tokens against 205K.
Has any benchmark tested both MiniMax M2.1 and Qwen3.8 Flash?
No benchmark has tested both yet. MiniMax M2.1 has results on LiveCodeBench (Vals AI), SWE-bench Verified (Vals AI) and LiveCodeBench (Artificial Analysis run); Qwen3.8 Flash on LiveBench coding, LiveBench research and LiveBench browser. Compare them on price and context instead. Data as of October 22, 2026.