GPT-6.1 Terra vs Mistral Large 3

OpenAI · US  |  Mistral · France · Updated June 2026

Quick verdict

Pick GPT-6.1 Terra for $1/$5 per million tokens (cached input $0.05) - half the price of gpt-6.1 sol and gpt-5.6 terra or terminal-bench 4.0 of 50.3% at maximum reasoning effort, versus 21.5% for gpt-5.6 terra (openai-reported). Pick Mistral Large 3 for open-weight (apache 2.0), self-hostable or strong multilingual performance. Choose Mistral Large 3 if you need self-hosting or data privacy; GPT-6.1 Terra if you want a managed API.

GPT-6.1 Terra (OpenAI, US) and Mistral Large 3 (Mistral, France) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. GPT-6.1 Terra is openAI's October 26, 2026 mid-tier model - a 1.05M-context, computer-use-capable GPT at $1/$5 per million tokens, half the price of its predecessor. Mistral Large 3 is france's frontier contender — strong multilingual model with European data residency. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.

Key differences at a glance

Side-by-side specs

SpecGPT-6.1 TerraMistral Large 3
ProviderOpenAI (US) Mistral (France)
ReleasedOctober 26, 2026 December 2, 2025
Context window1.05M tokens (~1,575 pages) 256K (~384 pages)
Price (in/out)$1/$5 per 1M tokens $0.5/$1.5 per 1M tokens
Open weight?No — API only Yes — self-hostable
Modalitiestext, image, code text, image, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

$1/$5 per million tokens (cached input $0.05) - half the price of GPT-6.1 Sol and GPT-5.6 Terra

GPT-6.1 Terra

Its 1.05M tokens window holds about 4.1× more than Mistral Large 3's 256K in a single prompt.

Terminal-Bench 4.0 of 50.3% at maximum reasoning effort, versus 21.5% for GPT-5.6 Terra (OpenAI-reported)

GPT-6.1 Terra

Mistral Large 3 is comparatively weak here — less benchmark coverage

1.05M-token context with up to 128K output tokens, plus image input and computer use via the Responses API

GPT-6.1 Terra

Mistral Large 3 is comparatively weak here — smaller context than US/China frontier

Open-weight (Apache 2.0), self-hostable

Mistral Large 3

Open weights make this possible at all — GPT-6.1 Terra is API-only, so it cannot leave the vendor's servers.

Strong multilingual performance

Mistral Large 3

France's frontier contender — strong multilingual model with European data residency — and it runs cheaper at $0.5/$1.5 per 1M tokens.

Efficient inference

Mistral Large 3

France's frontier contender — strong multilingual model with European data residency — and its weights are open while GPT-6.1 Terra is API-only.

Lowest cost at scale

Mistral Large 3

At $0.5/$1.5 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.

Largest single-prompt input

GPT-6.1 Terra

Its 1.05M tokens window is about 4.1× larger than Mistral Large 3's 256K, fitting roughly 1,575 pages in one prompt.

Which should you pick?

A cost-sensitive startup shipping high volume

→ Mistral Large 3

At $0.5/$1.5 per 1M tokens it undercuts GPT-6.1 Terra, and on millions of tokens that margin decides the monthly bill.

Someone analysing very long documents or codebases

→ GPT-6.1 Terra

Larger 1.05M tokens window fits more in one prompt.

A team with data-privacy or self-hosting needs

→ Mistral Large 3

Open weights let you run it on your own hardware; GPT-6.1 Terra is API-only.

Anyone whose priority is $1/$5 per million tokens (cached input $0.05) - half the price of gpt-6.1 sol and gpt-5.6 terra

→ GPT-6.1 Terra

It is specifically built for that.

Anyone whose priority is open-weight (apache 2.0), self-hostable

→ Mistral Large 3

That is its strongest area.

An enterprise with regional data-residency rules

→ GPT-6.1 Terra or Mistral Large 3

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

GPT-6.1 Terra: where it fits

OpenAI's October 26, 2026 mid-tier model - a 1.05M-context, computer-use-capable GPT at $1/$5 per million tokens, half the price of its predecessor. Released October 26, 2026 by OpenAI, it is built for $1/$5 per million tokens (cached input $0.05) - half the price of GPT-6.1 Sol and GPT-5.6 Terra, terminal-Bench 4.0 of 50.3% at maximum reasoning effort, versus 21.5% for GPT-5.6 Terra (OpenAI-reported), 1.05M-token context with up to 128K output tokens, plus image input and computer use via the Responses API, and error rate on OpenAI's hard-prompt set falls from 53.6% (GPT-5.6 Terra) to 16.7% at low effort and 4.3% at max effort.

Its trade-offs are real: openAI still positions Sol and Astra as the higher-capability choices for demanding coding problems, requests above 272K input tokens are billed at 2x input and 1.5x output for the whole request, closed weights and no fine-tuning support, and benchmark figures are vendor-reported; no SWE-bench Verified or MRCR numbers published. At $1 in / $5 out per million tokens, it sits in the budget price band.

Mistral Large 3: where it fits

France's frontier contender — strong multilingual model with European data residency. Released December 2, 2025 by Mistral, it is built for open-weight (Apache 2.0), self-hostable, strong multilingual performance, efficient inference, and function calling.

Its trade-offs: smaller context than US/China frontier, and less benchmark coverage. At $0.5 in / $1.5 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 3 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. GPT-6.1 Terra 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 GPT-6.1 Terra and Mistral Large 3 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 GPT-6.1 Terra or Mistral Large 3 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, GPT-6.1 Terra leans toward $1/$5 per million tokens (cached input $0.05) - half the price of gpt-6.1 sol and gpt-5.6 terra while Mistral Large 3 leans toward open-weight (apache 2.0), self-hostable, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, GPT-6.1 Terra or Mistral Large 3?

Mistral Large 3 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while GPT-6.1 Terra is API-metered at $1/$5 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?

GPT-6.1 Terra — 1.05M tokens vs 256K, about 4.1× larger. Useful only if the model actually reasons over the full window, which not all do.

Can I use both GPT-6.1 Terra and Mistral Large 3 together?

Yes — a multi-model platform like LumiChats gives you GPT-6.1 Terra, Mistral Large 3 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, GPT-6.1 Terra or Mistral Large 3?

GPT-6.1 Terra — released October 26, 2026, about 11 months after Mistral Large 3.

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.