Mistral Large 4 vs Qwen 3.6 Plus
Mistral AI · France | Alibaba · China · Updated June 2026
Quick verdict
Pick Mistral Large 4 for mistral's largest model to date — 1.05t total parameters, 49b active per token (granular moe), plus a 1.6b-parameter vision encoder or trained from scratch on 3,800 nvidia grace blackwell gpus in mistral's own european data centers, across 160+ languages. Pick Qwen 3.6 Plus for strong gpqa diamond science reasoning or open-weight and budget-friendly. On a tight budget at scale, Qwen 3.6 Plus is the value pick.
Mistral Large 4 (Mistral AI, France) and Qwen 3.6 Plus (Alibaba, China) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. Mistral Large 4 is mistral's October 6, 2026 public preview of 'Le Chonk' — a 1.05T-parameter, natively multimodal MoE model with open weights planned by month's end. Qwen 3.6 Plus is alibaba's open-weight contender — surprising benchmark wins at a budget price. Their biggest split is price, and the breakdown below shows exactly how that plays out for your workload.
Key differences at a glance
- ▸Price: Qwen 3.6 Plus is about 2.1× cheaper on input ($0.325/$1.95 per 1M tokens vs $0.68/$2.09 per 1M tokens) — meaningful once you are processing millions of tokens a month.
- ▸Context window: both advertise 1M tokens (~1,500 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
- ▸Recency: Mistral Large 4 is the newer model by about 6 months (released October 6, 2026), usually meaning fresher training data and capabilities.
- ▸Ecosystem: this is a France-vs-China matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
| Spec | Mistral Large 4 | Qwen 3.6 Plus |
|---|---|---|
| Provider | Mistral AI (France) | Alibaba (China) |
| Released | October 6, 2026 | April 2, 2026 |
| Context window | 1M tokens (~1,500 pages) | 1M (~1,500 pages) |
| Price (in/out) | $0.68/$2.09 per 1M tokens | $0.325/$1.95 per 1M tokens |
| Open weight? | No — API only | No — API only |
| Modalities | text, image, code | text, image, code |
| SWE-Bench Verified | Not published | 78.8% |
| MRCR v2 @ 1M | Not published | Not published |
Who wins what
Mistral's largest model to date — 1.05T total parameters, 49B active per token (granular MoE), plus a 1.6B-parameter vision encoder
Mistral Large 4
Mistral's October 6, 2026 public preview of 'Le Chonk' — a 1.05T-parameter, natively multimodal MoE model with open weights planned by month's end — and it is the newer of the two.
Trained from scratch on 3,800 Nvidia Grace Blackwell GPUs in Mistral's own European data centers, across 160+ languages
Mistral Large 4
Mistral Large 4 lists trained from scratch on 3,800 Nvidia Grace Blackwell GPUs in Mistral's own European data centers, across 160+ languages among its strengths; Qwen 3.6 Plus does not.
Hybrid instruct/reasoning design — answers quickly by default or switches into step-by-step reasoning
Mistral Large 4
Mistral Large 4 lists hybrid instruct/reasoning design — answers quickly by default or switches into step-by-step reasoning among its strengths; Qwen 3.6 Plus does not.
Strong GPQA Diamond science reasoning
Qwen 3.6 Plus
Alibaba's open-weight contender — surprising benchmark wins at a budget price — and it runs cheaper at $0.325/$1.95 per 1M tokens.
Open-weight and budget-friendly
Qwen 3.6 Plus
At $0.325/$1.95 per 1M tokens it undercuts Mistral Large 4 ($0.68/$2.09 per 1M tokens), and that gap compounds at volume.
1M context
Qwen 3.6 Plus
Qwen 3.6 Plus lists 1M context among its strengths; Mistral Large 4 does not.
Lowest cost at scale
Qwen 3.6 Plus
At $0.325/$1.95 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Qwen 3.6 Plus
At $0.325/$1.95 per 1M tokens it undercuts Mistral Large 4, and on millions of tokens that margin decides the monthly bill.
Anyone whose priority is mistral's largest model to date — 1.05t total parameters, 49b active per token (granular moe), plus a 1.6b-parameter vision encoder
→ Mistral Large 4
It is specifically built for that.
Anyone whose priority is strong gpqa diamond science reasoning
→ Qwen 3.6 Plus
That is its strongest area.
An enterprise with regional data-residency rules
→ Qwen 3.6 Plus or Mistral Large 4
Origin (France vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
Mistral Large 4: where it fits
Mistral's October 6, 2026 public preview of 'Le Chonk' — a 1.05T-parameter, natively multimodal MoE model with open weights planned by month's end. Released October 6, 2026 by Mistral AI, it is built for mistral's largest model to date — 1.05T total parameters, 49B active per token (granular MoE), plus a 1.6B-parameter vision encoder, trained from scratch on 3,800 Nvidia Grace Blackwell GPUs in Mistral's own European data centers, across 160+ languages, hybrid instruct/reasoning design — answers quickly by default or switches into step-by-step reasoning, and open weights planned by end of October 2026, which would make it among the largest open-weight models available.
Its trade-offs are real: still a public preview, not a finished release — Mistral says training is ongoing with 'no signs of saturation', weights not yet shipped as of mid-October 2026 — API-only for now despite the open-weight framing, launch pricing ($0.68/$2.09 per million) is a preview discount — Mistral's own model page lists a $1.36/$4.18 list price once the promotion ends, and scores 61.7% on DeepSWE v1.1, trailing DeepSeek V4.1 Flash (74.2%) and Kimi K3 (68.0%) on that coding benchmark. At $0.68 in / $2.09 out per million tokens, it sits in the budget price band.
Qwen 3.6 Plus: where it fits
Alibaba's open-weight contender — surprising benchmark wins at a budget price. Released April 2, 2026 by Alibaba, it is built for strong GPQA Diamond science reasoning, open-weight and budget-friendly, 1M context, and multilingual coverage.
Its trade-offs: less Western ecosystem tooling, and benchmark coverage still maturing. At $0.325 in / $1.95 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
This is less "which is smarter" and more "which ecosystem fits." Mistral Large 4 (France) and Qwen 3.6 Plus (China) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Qwen 3.6 Plus is the cheaper option, which matters at volume. The pragmatic move is to run one real task through both and judge the outputs against your own constraints — including where your data is allowed to be processed.
Want both Mistral Large 4 and Qwen 3.6 Plus 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 pricingFrequently asked questions
Is Mistral Large 4 or Qwen 3.6 Plus better for coding?
Public SWE-Bench figures are not available for Mistral Large 4, so the honest test is your own repository — run an identical real bug through both. By design, Mistral Large 4 leans toward mistral's largest model to date — 1.05t total parameters, 49b active per token (granular moe), plus a 1.6b-parameter vision encoder while Qwen 3.6 Plus leans toward strong gpqa diamond science reasoning, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Mistral Large 4 or Qwen 3.6 Plus?
Qwen 3.6 Plus is cheaper — $0.68/$2.09 per 1M tokens vs $0.325/$1.95 per 1M tokens, roughly 2.1× apart on input.
Which has the bigger context window?
Both advertise 1M tokens (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Mistral Large 4 and Qwen 3.6 Plus together?
Yes — a multi-model platform like LumiChats gives you Mistral Large 4, Qwen 3.6 Plus 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, Mistral Large 4 or Qwen 3.6 Plus?
Mistral Large 4 — released October 6, 2026, about 6 months after Qwen 3.6 Plus.
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.