Model comparison

MiniMax M2.7 vs Qwen3-235B-A22B

MiniMax against Qwen, compared on context, price, and verified benchmark results.

Catalog record checked September 26, 2026Individual provider fields may changeEvidence confidence: High — see receipts below

MiniMax

MiniMax M2.7

Balanced · Open weights

Qwen

Qwen3-235B-A22B

Balanced · Open weights

AI model capability comparison
Specification	MiniMax M2.7	Qwen3-235B-A22B
Provider
Provider	MiniMax	Qwen
Tier
Tier	Balanced	Balanced
Context window
Context window	Winner: 205K	128K
Max output
Max output	Not verifiedUnverified	33K
Input / 1M tokens
Input / 1M tokens	Winner: $0.30	$0.70
Output / 1M tokens
Output / 1M tokens	Winner: $1.20	$2.80
Weights
Weights	Open	Open
Parameters
Parameters	Not disclosedUnverified	235B total / 22B active (MoE)
Reasoning levels
Reasoning levels	Not verifiedUnverified	low, high, max
Modalities
Modalities	text	text
License
License	Not disclosedUnverified	Apache 2.0
API model id
API model id	MiniMax-M2.7	qwen3-235b-a22b
Released
Released	March 18, 2026	April 29, 2025
Artificial Analysis Intelligence Index (2026-09-26)
Artificial Analysis Intelligence Index (2026-09-26)	Winner: 22.8	9.5

Prices are USD per million tokens at standard rates, excluding batch and caching discounts. Bold indicates the better figure where one is objectively better. Values we could not confirm from the provider are shown as “Not verified” rather than estimated.

Benchmark receipts

Where each score comes from, and how far it can be compared across models.

2026-09-26
Artificial Analysis (Reasoning, AA-estimated)
Composite index blending reasoning, knowledge, and coding evals into one 0–100 score.
Comparable with caveatOnly same-version scores are comparable. v4.3.2 was rebaselined (the top score fell from 66 on v4.1.1 to ~58), so v4.1.1 figures must not be compared with v4.3.2 figures — check measuredAt.

Pricing tiers

MiniMax M2.7: $0.30/$1.20 per MTok on MiniMax's pay-as-you-go API; cache read $0.06, cache write $0.375. Open weights on Hugging Face (licence terms not re-verified).

Qwen3-235B-A22B: Model Studio International $0.70 input / $2.80 output per MTok (non-thinking); thinking-mode output $8.40. Open weights (Apache 2.0) for self-hosting; 32,768-token recommended output.

BalancedOpen weightsRecord checked September 26, 2026

MiniMax M2.7

MiniMax M2.7 is MiniMax's current text-only open-weight model with a 204,800-token context, priced like M3.

Best for

Text-only agents
Open-weight deployments
Cost-sensitive coding

Watch out

Text-only and a 204,800-token context — M3 has 1M context and multimodal input at the same $0.30/$1.20 list price.

BalancedOpen weightsRecord checked September 26, 2026

Qwen3-235B-A22B

Qwen3-235B-A22B is Alibaba's widely deployed open-weight MoE — 235B/22B, strong price-performance.

Best for

Open-weight deployments
Self-hosting
Multilingual

Watch out

Needs multi-GPU for the 235B total; hosted rates vary.

When the cheaper one wins

MiniMax M2.7 is cheaper on output at $1.20 per million tokens against $2.80 for Qwen3-235B-A22B — about 2.3×. Use the cheaper tier for classification, extraction, summarisation, and any task where the expensive model’s extra score does not change the accepted output. The expensive one only pays if your hardest task actually fails on the cheap tier. These are standard-tier API rates, excluding batch and cache discounts.

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Evidence confidence: High

How strong and complete the evidence behind this comparison is — not a prediction of which model is better.

Pricing verified on both sides — Input and output rates are verified for both models.
2/5 core specs verified on both sides — Not published for at least one side: max output, parameter count, reasoning levels.
1 shared named benchmark with differing scores — Measured on: Artificial Analysis Intelligence Index.
Verified within the last 90 days — Newest catalog check was 2 days ago.
Both models carry source citations — Each side has at least two catalog sources on record.

Source receipts

Each catalog figure was checked against the provider or an independent second source on the date shown.

MiniMax M2.7: MiniMax — model release notes (M2.7, 2026-03-18) (accessed 2026-09-26)
MiniMax M2.7: MiniMax pay-as-you-go pricing (M2.7 $0.30/$1.20) (accessed 2026-09-26)
MiniMax M2.7: Hugging Face — MiniMaxAI/MiniMax-M2.7 (accessed 2026-09-26)
Qwen3-235B-A22B: HuggingFace — Qwen3-235B-A22B (accessed 2026-08-29)
Qwen3-235B-A22B: Qwen — Qwen3 (accessed 2026-08-29)
Qwen3-235B-A22B: Alibaba Cloud Model Studio pricing (qwen3-235b-a22b $0.70/$2.80, thinking $8.40) (accessed 2026-09-26)

Related comparisons

Diving deeper on one model? MiniMax M2.7 · Qwen3-235B-A22B

Common questions

MiniMax M2.7 vs Qwen3-235B-A22B

Answered from the verified figures on this page rather than general guidance.

Is MiniMax M2.7 or Qwen3-235B-A22B cheaper for input?

MiniMax M2.7 is cheaper at $0.30 per million input tokens, against $0.70 for Qwen3-235B-A22B — roughly 2.3× the price. Output tokens usually dominate a real bill, so weigh the output rate more heavily than the input rate. These are base rates; MiniMax M2.7 has tiered pricing: $0.30/$1.20 per MTok on MiniMax's pay-as-you-go API; cache read $0.06, cache write $0.375. Open weights on Hugging Face (licence terms not re-verified). Qwen3-235B-A22B has tiered pricing: Model Studio International $0.70 input / $2.80 output per MTok (non-thinking); thinking-mode output $8.40. Open weights (Apache 2.0) for self-hosting; 32,768-token recommended output.

Is MiniMax M2.7 or Qwen3-235B-A22B cheaper for output?

MiniMax M2.7 is cheaper at $1.20 per million output tokens, against $2.80 for Qwen3-235B-A22B — roughly 2.3× the price. Output tokens usually dominate a real bill, so weigh the output rate more heavily than the input rate. These are base rates; MiniMax M2.7 has tiered pricing: $0.30/$1.20 per MTok on MiniMax's pay-as-you-go API; cache read $0.06, cache write $0.375. Open weights on Hugging Face (licence terms not re-verified). Qwen3-235B-A22B has tiered pricing: Model Studio International $0.70 input / $2.80 output per MTok (non-thinking); thinking-mode output $8.40. Open weights (Apache 2.0) for self-hosting; 32,768-token recommended output.

Which has the larger context window, MiniMax M2.7 or Qwen3-235B-A22B?

MiniMax M2.7 accepts 205K tokens against 128K for Qwen3-235B-A22B. This only matters if you routinely send very long documents or large codebases.

Should I use MiniMax M2.7 or Qwen3-235B-A22B?

Both sit in the balanced tier, so the choice usually comes down to price and context rather than capability. MiniMax M2.7 suits text-only agents; Qwen3-235B-A22B suits open-weight deployments.

Next step

Choosing between them

The verified figures that separate this pair, computed from the catalog rather than restated boilerplate.

Input price: MiniMax M2.7 costs $0.30 per 1M tokens versus $0.70 for Qwen3-235B-A22B — a 2.3x difference at the headline tier.
Context: MiniMax M2.7 takes 205K against 128K for Qwen3-235B-A22B — only decisive if your prompts approach the smaller window.

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