Gemini 4 Carbon vs Mistral Large 4

Google · US  |  Mistral AI · France · Updated June 2026

Quick verdict

Pick Gemini 4 Carbon for ranked first on the artificial analysis intelligence index v5.0 with 59 at launch (artificial analysis now shows 60) or google-reported 88.2% on sec-bench pro and 54.8% on exploitgym for vulnerability discovery and exploit validation. Pick Mistral Large 4 for mistral's largest model to date — about 1t total parameters, 49b active per token (52b with embeddings and output layers), 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. Choose Mistral Large 4 if you need self-hosting or data privacy; Gemini 4 Carbon if you want a managed API.

Gemini 4 Carbon (Google, US) and Mistral Large 4 (Mistral AI, France) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. Gemini 4 Carbon is google's October 28, 2026 limited release for cyber defenders - top of the Artificial Analysis index at launch, priced at $2/$10 introductory, with no public API date yet. Mistral Large 4 is mistral's 'Le Chonk' — a 1T-parameter, natively multimodal MoE model previewed October 6, 2026, with open weights published October 29 and API pricing of $0.70/$2.10. They diverge most on price and open vs. closed weights — each quantified below from the models' real specs.

Key differences at a glance

Side-by-side specs

SpecGemini 4 CarbonMistral Large 4
ProviderGoogle (US) Mistral AI (France)
ReleasedOctober 28, 2026 October 6, 2026
Context window1M tokens (~1,500 pages) 1M tokens (~1,500 pages)
Price (in/out)$2/$10 per 1M tokens $0.7/$2.1 per 1M tokens
Open weight?No — API only Yes — self-hostable
Modalitiestext, image, audio, video, code text, image, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

Ranked first on the Artificial Analysis Intelligence Index v5.0 with 59 at launch (Artificial Analysis now shows 60)

Gemini 4 Carbon

Mistral Large 4 is comparatively weak here — launched as a public preview — Mistral's launch post said the model was still improving

Google-reported 88.2% on SEC-bench Pro and 54.8% on ExploitGym for vulnerability discovery and exploit validation

Gemini 4 Carbon

Mistral Large 4 is comparatively weak here — scores 61.7% on DeepSWE v1.1, trailing DeepSeek V4.1 Flash (74.2%) and Kimi K3 (68.0%) on that coding benchmark

Google-reported 71.0% on CWE-bench for patching

Gemini 4 Carbon

Google's October 28, 2026 limited release for cyber defenders - top of the Artificial Analysis index at launch, priced at $2/$10 introductory, with no public API date yet — and it is the newer of the two.

Mistral's largest model to date — about 1T total parameters, 49B active per token (52B with embeddings and output layers), plus a 1.6B-parameter vision encoder

Mistral Large 4

Gemini 4 Carbon is comparatively weak here — no public API model listing yet, so most users cannot call it today

Trained from scratch on 3,800 Nvidia Grace Blackwell GPUs in Mistral's own European data centers, across 160+ languages

Mistral Large 4

Mistral's 'Le Chonk' — a 1T-parameter, natively multimodal MoE model previewed October 6, 2026, with open weights published October 29 and API pricing of $0.70/$2.10 — and it runs cheaper at $0.7/$2.1 per 1M tokens.

Hybrid instruct/reasoning design — answers quickly by default or switches into step-by-step reasoning

Mistral Large 4

Mistral's 'Le Chonk' — a 1T-parameter, natively multimodal MoE model previewed October 6, 2026, with open weights published October 29 and API pricing of $0.70/$2.10 — and its weights are open while Gemini 4 Carbon is API-only.

Lowest cost at scale

Mistral Large 4

At $0.7/$2.1 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

→ Mistral Large 4

At $0.7/$2.1 per 1M tokens it undercuts Gemini 4 Carbon, and on millions of tokens that margin decides the monthly bill.

A team with data-privacy or self-hosting needs

→ Mistral Large 4

Open weights let you run it on your own hardware; Gemini 4 Carbon is API-only.

Anyone whose priority is ranked first on the artificial analysis intelligence index v5.0 with 59 at launch (artificial analysis now shows 60)

→ Gemini 4 Carbon

It is specifically built for that.

Anyone whose priority is mistral's largest model to date — about 1t total parameters, 49b active per token (52b with embeddings and output layers), plus a 1.6b-parameter vision encoder

→ Mistral Large 4

That is its strongest area.

An enterprise with regional data-residency rules

→ Gemini 4 Carbon or Mistral Large 4

Origin (US vs France) affects where data is processed and which compliance regime applies — check the provider's terms for your region.

Gemini 4 Carbon: where it fits

Google's October 28, 2026 limited release for cyber defenders - top of the Artificial Analysis index at launch, priced at $2/$10 introductory, with no public API date yet. Released October 28, 2026 by Google, it is built for ranked first on the Artificial Analysis Intelligence Index v5.0 with 59 at launch (Artificial Analysis now shows 60), google-reported 88.2% on SEC-bench Pro and 54.8% on ExploitGym for vulnerability discovery and exploit validation, google-reported 71.0% on CWE-bench for patching, and introductory $2/$10 per million tokens, matching Gemini 4 Argon, with cached input 95% off.

Its trade-offs are real: limited release: rolling out to a subset of cyber defenders, then trusted partners via the Fairwind Program, with no date for developers or consumers, no public API model listing yet, so most users cannot call it today, introductory pricing rises to $4/$20 afterward, and Google has not said when that happens, and google has not published context or modality specs - the 1M window and modalities shown come from Artificial Analysis and Vals. At $2 in / $10 out per million tokens, it sits in the mid price band.

Mistral Large 4: where it fits

Mistral's 'Le Chonk' — a 1T-parameter, natively multimodal MoE model previewed October 6, 2026, with open weights published October 29 and API pricing of $0.70/$2.10. Released October 6, 2026 by Mistral AI, it is built for mistral's largest model to date — about 1T total parameters, 49B active per token (52B with embeddings and output layers), 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 on Hugging Face since October 29, 2026, with an NVFP4 checkpoint for Blackwell GPUs, making it among the largest open-weight models available.

Its trade-offs: launched as a public preview — Mistral's launch post said the model was still improving, mistral Ecosystem Open-Weight License is a modified MIT license: selling hosted access to third parties needs a separate commercial license, self-hosting a 1T-parameter MoE needs datacenter-class GPUs, 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 $0.7 in / $2.1 out per million tokens, it sits in the budget price band.

The bottom line for this matchup

The defining split here is open vs. closed. Mistral Large 4 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Gemini 4 Carbon gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.

Want both Gemini 4 Carbon and Mistral Large 4 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 Gemini 4 Carbon or Mistral Large 4 better for coding?

Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, Gemini 4 Carbon leans toward ranked first on the artificial analysis intelligence index v5.0 with 59 at launch (artificial analysis now shows 60) while Mistral Large 4 leans toward mistral's largest model to date — about 1t total parameters, 49b active per token (52b with embeddings and output layers), plus a 1.6b-parameter vision encoder, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, Gemini 4 Carbon or Mistral Large 4?

Mistral Large 4 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Gemini 4 Carbon is API-metered at $2/$10 per 1M tokens. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.

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 Gemini 4 Carbon and Mistral Large 4 together?

Yes — a multi-model platform like LumiChats gives you Gemini 4 Carbon, Mistral Large 4 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, Gemini 4 Carbon or Mistral Large 4?

Gemini 4 Carbon — released October 28, 2026, about 22 days after Mistral Large 4.

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.