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MiniMax M1 vs Qwen3 30B A3B Instruct 2507

MiniMax M1 leads Qwen3 30B A3B Instruct 2507 on the Artificial Analysis Intelligence Index, 11.7 to 7.5, and Qwen3 30B A3B Instruct 2507 costs 7.3x less per output token ($0.30 vs $2.20 per million). Updated October 22, 2026; 29 benchmarks have a result for both.

MiniMax M1MiniMax
Coding
No data
Overall
No data
Output $/M
$2.20
1
Qwen3 30B A3B Instruct 2507Qwen
Coding
No data
Overall
41.5
Output $/M
$0.30
28
vs boards won of 29 shared

MiniMax M1 or Qwen3 30B A3B Instruct 2507: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick MiniMax M1 for a larger context window (1M against 262K tokens) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Shared results
29
MiniMax M1 only
0
Qwen3 30B A3B Instruct 2507 only
16
Like-for-like categories
6 of 9

Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.

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.

At a glance

Coding index
MiniMax M1 not benchmarked, Qwen3 30B A3B Instruct 2507 not benchmarked.
Widest category
Reasoning, 10.6 points apart on average over 3 shared benchmarks.
Widest single gap
LMArena Text: Japanese: MiniMax M1 1217 against Qwen3 30B A3B Instruct 2507 1337, 20.1 points apart on a 0 to 100 scale.
Output price
MiniMax M1 $2.20 against Qwen3 30B A3B Instruct 2507 $0.30 per million output tokens, 7.3x apart.
Context window
MiniMax M1 takes 1M tokens, Qwen3 30B A3B Instruct 2507 262K.

Benchmark by benchmark

First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.

Boards won, where both have a result
CategoryMiniMax M1BarsQwen3 30B A3B Instruct 2507Ties
Coding02
Intelligence10
Reasoning03
Math02
Knowledge04
General017
All shared boards128
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
Coding benchmarks for MiniMax M1 and Qwen3 30B A3B Instruct 2507
BenchmarkMiniMax M1Qwen3 30B A3B Instruct 2507Leader
LiveCodeBench (Artificial Analysis run)Not measured70.7%Only Qwen3 30B A3B Instruct 2507 measured
SciCodeNot measured33.0%Only Qwen3 30B A3B Instruct 2507 measured
Terminal-Bench Hard (Artificial Analysis run)Not measured6.1%Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: coding13591416Qwen3 30B A3B Instruct 2507
LMArena Text: software and IT13591417Qwen3 30B A3B Instruct 2507
Neither model has a result on the other 38 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for MiniMax M1 and Qwen3 30B A3B Instruct 2507
BenchmarkMiniMax M1Qwen3 30B A3B Instruct 2507Leader
AA Intelligence Index11.77.5MiniMax M1
Neither model has a result on the other 1 board here
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Agentic work benchmarks for MiniMax M1 and Qwen3 30B A3B Instruct 2507
BenchmarkMiniMax M1Qwen3 30B A3B Instruct 2507Leader
τ²-Bench TelecomNot measured28.1%Only Qwen3 30B A3B Instruct 2507 measured
Berkeley Function Calling Leaderboard (BFCL)Not measured41.4%Only Qwen3 30B A3B Instruct 2507 measured
Neither model has a result on the other 40 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
Reasoning benchmarks for MiniMax M1 and Qwen3 30B A3B Instruct 2507
BenchmarkMiniMax M1Qwen3 30B A3B Instruct 2507Leader
GPQA Diamond (Artificial Analysis run)Not measured70.7%Only Qwen3 30B A3B Instruct 2507 measured
Humanity's Last Exam (Artificial Analysis run)Not measured10.3%Only Qwen3 30B A3B Instruct 2507 measured
GPQA Diamond (Epoch AI run)Not measured55.6%Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: hard prompts13391398Qwen3 30B A3B Instruct 2507
LMArena Text: expert13171397Qwen3 30B A3B Instruct 2507
LMArena Text: hard prompts in English13531406Qwen3 30B A3B Instruct 2507
Neither model has a result on the other 17 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for MiniMax M1 and Qwen3 30B A3B Instruct 2507
BenchmarkMiniMax M1Qwen3 30B A3B Instruct 2507Leader
AA Math IndexNot measured66.3Only Qwen3 30B A3B Instruct 2507 measured
AIME 2025 (Artificial Analysis run)Not measured66.3%Only Qwen3 30B A3B Instruct 2507 measured
OTIS Mock AIMENot measured62.2%Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: math13611394Qwen3 30B A3B Instruct 2507
LMArena Text: mathematical work13631411Qwen3 30B A3B Instruct 2507
Neither model has a result on the other 9 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for MiniMax M1 and Qwen3 30B A3B Instruct 2507
BenchmarkMiniMax M1Qwen3 30B A3B Instruct 2507Leader
MMLU Pro (Artificial Analysis run)Not measured80.5%Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text: science13541393Qwen3 30B A3B Instruct 2507
LMArena Text: medicine and healthcare13551392Qwen3 30B A3B Instruct 2507
LMArena Text: legal and government13371387Qwen3 30B A3B Instruct 2507
LMArena Text: business and finance13191389Qwen3 30B A3B Instruct 2507
Neither model has a result on the other 15 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for MiniMax M1 and Qwen3 30B A3B Instruct 2507
BenchmarkMiniMax M1Qwen3 30B A3B Instruct 2507Leader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index017
General benchmarks for MiniMax M1 and Qwen3 30B A3B Instruct 2507
BenchmarkMiniMax M1Qwen3 30B A3B Instruct 2507Leader
IFBenchNot measured50.7%Only Qwen3 30B A3B Instruct 2507 measured
Long context reasoning (AA-LCR)Not measured61.3%Only Qwen3 30B A3B Instruct 2507 measured
DTBenchNot measured67.2%Only Qwen3 30B A3B Instruct 2507 measured
LMCANot measured22.4%Only Qwen3 30B A3B Instruct 2507 measured
LMArena Text13431384Qwen3 30B A3B Instruct 2507
LMArena Text: instruction following13121363Qwen3 30B A3B Instruct 2507
LMArena Text: creative writing12971317Qwen3 30B A3B Instruct 2507
LMArena Text: English13631391Qwen3 30B A3B Instruct 2507
LMArena Text: non-English13191372Qwen3 30B A3B Instruct 2507
LMArena Text: Chinese13601432Qwen3 30B A3B Instruct 2507
LMArena Text: German13501379Qwen3 30B A3B Instruct 2507
LMArena Text: Japanese12171337Qwen3 30B A3B Instruct 2507
LMArena Text: Korean12661330Qwen3 30B A3B Instruct 2507
LMArena Text: French13701419Qwen3 30B A3B Instruct 2507
LMArena Text: Spanish13531404Qwen3 30B A3B Instruct 2507
LMArena Text: Russian13291369Qwen3 30B A3B Instruct 2507
LMArena Text: Polish13291353Qwen3 30B A3B Instruct 2507
LMArena Text: multi-turn13351378Qwen3 30B A3B Instruct 2507
LMArena Text: longer queries13261378Qwen3 30B A3B Instruct 2507
LMArena Text: writing and language13111336Qwen3 30B A3B Instruct 2507
LMArena Text: entertainment and media13031334Qwen3 30B A3B Instruct 2507
Neither model has a result on the other 27 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for MiniMax M1 and Qwen3 30B A3B Instruct 2507
BenchmarkMiniMax M1Qwen3 30B A3B Instruct 2507Leader
Neither model has a result on 5 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

MiniMax M1$0.0015Fits in one request
Qwen3 30B A3B Instruct 2507$0.0002Fits in one request

Qwen3 30B A3B Instruct 2507 costs less

Repository review

50K input + 3K output tokens

MiniMax M1$0.027Fits in one request
Qwen3 30B A3B Instruct 2507$0.0054Fits in one request

Qwen3 30B A3B Instruct 2507 costs less

Agent loop

200K input + 10K output tokens

MiniMax M1$0.102Fits in one request
Qwen3 30B A3B Instruct 2507$0.021Fits in one request

Qwen3 30B A3B Instruct 2507 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.

Specifications of MiniMax M1 and Qwen3 30B A3B Instruct 2507
SpecificationMiniMax M1Qwen3 30B A3B Instruct 2507
MakerMiniMaxQwen
WeightsNo public weights listedOpen weights
ReleasedJune 17, 2025July 29, 2025
Context window1M262K
Input $/Mtok$0.40$0.09
Output $/Mtok$2.20$0.30
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is MiniMax M1 better than Qwen3 30B A3B Instruct 2507 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick MiniMax M1 for a larger context window (1M against 262K tokens) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Which is cheaper, MiniMax M1 or Qwen3 30B A3B Instruct 2507?

MiniMax M1 costs $0.40 per million input tokens and $2.20 per million output tokens; Qwen3 30B A3B Instruct 2507 costs $0.09 and $0.30. Cost per solved task is known for neither of them.

Which has the bigger context window, MiniMax M1 or Qwen3 30B A3B Instruct 2507?

MiniMax M1, with 1M tokens against 262K.

How many benchmarks is the MiniMax M1 vs Qwen3 30B A3B Instruct 2507 comparison based on?

29 benchmarks have a result for both models as of October 22, 2026. MiniMax M1's coding index rests on 0 independent benchmarks and Qwen3 30B A3B Instruct 2507's on 0. Where only one model has a result, the page says so instead of naming a winner.

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