MiniMax M3.1 Flash vs Qwen3.6 35B A3B

MiniMax · China  |  Alibaba · China · Updated June 2026

Quick verdict

Pick MiniMax M3.1 Flash for $0.15/$0.60 per million tokens (cached $0.015) with flat pricing regardless of prompt length or 428b-parameter moe (about 23b active) with weights on hugging face from october 23, 2026. Pick Qwen3.6 35B A3B for extreme sparsity — only 3b of 35b parameters active per token, giving near-3b inference cost or runs at roughly 120 tokens per second on a single 24gb consumer gpu. On a tight budget at scale, Qwen3.6 35B A3B is the value pick.

MiniMax M3.1 Flash (MiniMax) and Qwen3.6 35B A3B (Alibaba) are two of the models people most often weigh against each other in 2026. MiniMax M3.1 Flash is miniMax's October 19, 2026 always-thinking agentic Flash model - 1M context, text/image/video input, $0.15/$0.60 and open weights under a community license. Qwen3.6 35B A3B is a sparse 35B mixture-of-experts running on 3B active parameters — strong agentic coding at near-3B cost on consumer hardware. They diverge most on price and context window — each quantified below from the models' real specs.

Key differences at a glance

Side-by-side specs

SpecMiniMax M3.1 FlashQwen3.6 35B A3B
ProviderMiniMax (China) Alibaba (China)
ReleasedOctober 19, 2026 April 16, 2026
Context window1M tokens (~1,500 pages) 256K (~393 pages)
Price (in/out)$0.15/$0.6 per 1M tokens Open weight (self-host / free)
Open weight?Yes — self-hostable Yes — self-hostable
Modalitiestext, image, video, code text, image, code
SWE-Bench VerifiedNot published 73.4%
MRCR v2 @ 1MNot published Not published

Who wins what

$0.15/$0.60 per million tokens (cached $0.015) with flat pricing regardless of prompt length

MiniMax M3.1 Flash

Its 1M tokens window holds about 3.8× more than Qwen3.6 35B A3B's 256K in a single prompt.

428B-parameter MoE (about 23B active) with weights on Hugging Face from October 23, 2026

MiniMax M3.1 Flash

Qwen3.6 35B A3B is comparatively weak here — loses to its smaller dense sibling Qwen3.6 27B on every coding benchmark, despite more total parameters

DeepSWE v1.1 of 73.7% and OSWorld V2 of 61.7 (MiniMax-reported)

MiniMax M3.1 Flash

MiniMax's October 19, 2026 always-thinking agentic Flash model - 1M context, text/image/video input, $0.15/$0.60 and open weights under a community license — and it carries the larger 1M tokens context.

Extreme sparsity — only 3B of 35B parameters active per token, giving near-3B inference cost

Qwen3.6 35B A3B

MiniMax M3.1 Flash is comparatively weak here — thinking is always on and default effort is max, which inflates output-token cost

Runs at roughly 120 tokens per second on a single 24GB consumer GPU

Qwen3.6 35B A3B

Qwen3.6 35B A3B lists runs at roughly 120 tokens per second on a single 24GB consumer GPU among its strengths; MiniMax M3.1 Flash does not.

Apache 2.0 weights with a 256K native context, extensible to about 1M via YaRN

Qwen3.6 35B A3B

Qwen3.6 35B A3B lists apache 2.0 weights with a 256K native context, extensible to about 1M via YaRN among its strengths; MiniMax M3.1 Flash does not.

Lowest cost at scale

Qwen3.6 35B A3B

Its weights are open, so at volume you pay for your own hardware instead of MiniMax M3.1 Flash's $0.15/$0.6 per 1M tokens.

Largest single-prompt input

MiniMax M3.1 Flash

Its 1M tokens window is about 3.8× larger than Qwen3.6 35B A3B's 256K, fitting roughly 1,500 pages in one prompt.

Which should you pick?

A cost-sensitive startup shipping high volume

→ Qwen3.6 35B A3B

At Open weight (self-host / free) it undercuts MiniMax M3.1 Flash, and on millions of tokens that margin decides the monthly bill.

Someone analysing very long documents or codebases

→ MiniMax M3.1 Flash

Larger 1M tokens window fits more in one prompt.

Anyone whose priority is $0.15/$0.60 per million tokens (cached $0.015) with flat pricing regardless of prompt length

→ MiniMax M3.1 Flash

It is specifically built for that.

Anyone whose priority is extreme sparsity — only 3b of 35b parameters active per token, giving near-3b inference cost

→ Qwen3.6 35B A3B

That is its strongest area.

MiniMax M3.1 Flash: where it fits

MiniMax's October 19, 2026 always-thinking agentic Flash model - 1M context, text/image/video input, $0.15/$0.60 and open weights under a community license. Released October 19, 2026 by MiniMax, it is built for $0.15/$0.60 per million tokens (cached $0.015) with flat pricing regardless of prompt length, 428B-parameter MoE (about 23B active) with weights on Hugging Face from October 23, 2026, deepSWE v1.1 of 73.7% and OSWorld V2 of 61.7 (MiniMax-reported), and artificial Analysis Intelligence Index of 42, 13 points above MiniMax M3.

Its trade-offs are real: thinking is always on and default effort is max, which inflates output-token cost, behind DeepSeek V4.1 Flash 1017 on Artificial Analysis's independent index, custom MiniMax Community license: attribution required, and products above $20M annual revenue need written authorization, and benchmarks are mostly self-reported; no SWE-bench Verified figure published. At $0.15 in / $0.6 out per million tokens, it sits in the budget price band.

Qwen3.6 35B A3B: where it fits

A sparse 35B mixture-of-experts running on 3B active parameters — strong agentic coding at near-3B cost on consumer hardware. Released April 16, 2026 by Alibaba, it is built for extreme sparsity — only 3B of 35B parameters active per token, giving near-3B inference cost, runs at roughly 120 tokens per second on a single 24GB consumer GPU, apache 2.0 weights with a 256K native context, extensible to about 1M via YaRN, and preserves its reasoning across turns, which cuts the overhead of agentic loops.

Its trade-offs: loses to its smaller dense sibling Qwen3.6 27B on every coding benchmark, despite more total parameters, its SWE-Bench score comes from Alibaba's internal scaffold rather than the standard public harness, and all 35B parameters must stay resident in VRAM even though only 3B compute per token. As an open-weight model, its running cost is your own hardware rather than a per-token fee.

The bottom line for this matchup

MiniMax M3.1 Flash and Qwen3.6 35B A3B overlap enough that the right pick depends on your specific job. Qwen3.6 35B A3B costs less per token; MiniMax M3.1 Flash holds the larger context; and each leads in its own area — MiniMax M3.1 Flash for $0.15/$0.60 per million tokens (cached $0.015) with flat pricing regardless of prompt length, Qwen3.6 35B A3B for extreme sparsity — only 3b of 35b parameters active per token, giving near-3b inference cost. Rather than crowning one, run the same hard task through both once and let the results decide.

Want both MiniMax M3.1 Flash and Qwen3.6 35B A3B without two subscriptions? LumiChats gives you these plus 40+ models under one ₹69/day pass (about $1/day) — draft with one, cross-check with the other.

See pricing

Frequently asked questions

Is MiniMax M3.1 Flash or Qwen3.6 35B A3B better for coding?

Public SWE-Bench figures are not available for MiniMax M3.1 Flash, so the honest test is your own repository — run an identical real bug through both. By design, MiniMax M3.1 Flash leans toward $0.15/$0.60 per million tokens (cached $0.015) with flat pricing regardless of prompt length while Qwen3.6 35B A3B leans toward extreme sparsity — only 3b of 35b parameters active per token, giving near-3b inference cost, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, MiniMax M3.1 Flash or Qwen3.6 35B A3B?

Qwen3.6 35B A3B is cheaper — $0.15/$0.6 per 1M tokens vs Open weight (self-host / free).

Which has the bigger context window?

MiniMax M3.1 Flash — 1M tokens vs 256K, about 3.8× larger. Useful only if the model actually reasons over the full window, which not all do.

Can I use both MiniMax M3.1 Flash and Qwen3.6 35B A3B together?

Yes — a multi-model platform like LumiChats gives you MiniMax M3.1 Flash, Qwen3.6 35B A3B and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.

Which is newer, MiniMax M3.1 Flash or Qwen3.6 35B A3B?

MiniMax M3.1 Flash — released October 19, 2026, about 6 months after Qwen3.6 35B A3B.

Related comparisons

Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.