Pick GPT-5.4 for strong general-purpose default or coding and software engineering. Pick Mistral Large 3 for european data-residency option or strong multilingual performance. On a tight budget at scale, Mistral Large 3 is the value pick.
GPT-5.4 (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-5.4 is openAI's 2026 workhorse — unifies Codex and GPT into a strong default that costs half of GPT-5.5. Mistral Large 3 is france's frontier contender — strong multilingual model with European data residency. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Price: nearly identical — $2.5/$15 per 1M tokens vs $2/$6 per 1M tokens. Cost will not be the deciding factor here.
Context window: GPT-5.4 holds 3.9× more — 1M (~1,500 pages) vs 256K (~384 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: GPT-5.4 is the newer model by about 32 days (released March 5, 2026), usually meaning fresher training data and capabilities.
Ecosystem: this is a US-vs-France matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Specifications
Spec
GPT-5.4
Mistral Large 3
Provider
OpenAI (US)
Mistral (France)
Released
March 5, 2026
February 2026
Context window
1M (~1,500 pages)
256K (~384 pages)
Price (in/out)
$2.5/$15 per 1M tokens
$2/$6 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Strong general-purpose default: GPT-5.4 — A core design strength of GPT-5.4.
Coding and software engineering: GPT-5.4 — A core design strength of GPT-5.4.
Document understanding and tool use: GPT-5.4 — A core design strength of GPT-5.4.
European data-residency option: Mistral Large 3 — A core design strength of Mistral Large 3.
Strong multilingual performance: Mistral Large 3 — A core design strength of Mistral Large 3.
Efficient inference: Mistral Large 3 — A core design strength of Mistral Large 3.
Lowest cost at scale: Mistral Large 3 — At $2/$6 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: GPT-5.4 — Its 1M window is about 3.9× larger, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Mistral Large 3 — At $2/$6 per 1M tokens it undercuts GPT-5.4, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: GPT-5.4 — Larger 1M window fits more in one prompt.
Anyone whose priority is strong general-purpose default: GPT-5.4 — It is specifically built for that.
Anyone whose priority is european data-residency option: Mistral Large 3 — That is its strongest area.
An enterprise with regional data-residency rules: GPT-5.4 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-5.4: where it fits
OpenAI's 2026 workhorse — unifies Codex and GPT into a strong default that costs half of GPT-5.5. Released March 5, 2026 by OpenAI, it is built for strong general-purpose default, coding and software engineering, document understanding and tool use, and 1M context with good token efficiency.
Its trade-offs are real: topped by GPT-5.5 on the hardest tasks, and pricier than open-weight rivals. At $2.5 in / $15 out per million tokens, it sits in the mid price band.
Mistral Large 3: where it fits
France's frontier contender — strong multilingual model with European data residency. Released February 2026 by Mistral, it is built for european data-residency option, strong multilingual performance, efficient inference, and function calling.
Its trade-offs: smaller context than US/China frontier, and less benchmark coverage. At $2 in / $6 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
This is less "which is smarter" and more "which ecosystem fits." GPT-5.4 (US) and Mistral Large 3 (France) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Mistral Large 3 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.
Frequently asked questions
Is GPT-5.4 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-5.4 leans toward strong general-purpose default while Mistral Large 3 leans toward european data-residency option, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-5.4 or Mistral Large 3?
Mistral Large 3 is cheaper — $2.5/$15 per 1M tokens vs $2/$6 per 1M tokens, roughly 1.3× apart on input.
Which has the bigger context window?
GPT-5.4 — 1M vs 256K, about 3.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GPT-5.4 and Mistral Large 3 together?
Yes — a multi-model platform like LumiChats gives you GPT-5.4, 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-5.4 or Mistral Large 3?
GPT-5.4 — released March 5, 2026, about 32 days after Mistral Large 3.
GPT-5.4 vs Mistral Large 3
OpenAI · US | Mistral · France · Updated June 2026
Quick verdict
Pick GPT-5.4 for strong general-purpose default or coding and software engineering. Pick Mistral Large 3 for european data-residency option or strong multilingual performance. On a tight budget at scale, Mistral Large 3 is the value pick.
GPT-5.4 (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-5.4 is openAI's 2026 workhorse — unifies Codex and GPT into a strong default that costs half of GPT-5.5. Mistral Large 3 is france's frontier contender — strong multilingual model with European data residency. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Price: nearly identical — $2.5/$15 per 1M tokens vs $2/$6 per 1M tokens. Cost will not be the deciding factor here.
▸Context window: GPT-5.4 holds 3.9× more — 1M (~1,500 pages) vs 256K (~384 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: GPT-5.4 is the newer model by about 32 days (released March 5, 2026), usually meaning fresher training data and capabilities.
▸Ecosystem: this is a US-vs-France matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
Spec
GPT-5.4
Mistral Large 3
Provider
OpenAI (US)
Mistral (France)
Released
March 5, 2026
February 2026
Context window
1M (~1,500 pages)
256K (~384 pages)
Price (in/out)
$2.5/$15 per 1M tokens
$2/$6 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Strong general-purpose default
GPT-5.4
A core design strength of GPT-5.4.
Coding and software engineering
GPT-5.4
A core design strength of GPT-5.4.
Document understanding and tool use
GPT-5.4
A core design strength of GPT-5.4.
European data-residency option
Mistral Large 3
A core design strength of Mistral Large 3.
Strong multilingual performance
Mistral Large 3
A core design strength of Mistral Large 3.
Efficient inference
Mistral Large 3
A core design strength of Mistral Large 3.
Lowest cost at scale
Mistral Large 3
At $2/$6 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
GPT-5.4
Its 1M window is about 3.9× larger, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Mistral Large 3
At $2/$6 per 1M tokens it undercuts GPT-5.4, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ GPT-5.4
Larger 1M window fits more in one prompt.
Anyone whose priority is strong general-purpose default
→ GPT-5.4
It is specifically built for that.
Anyone whose priority is european data-residency option
→ Mistral Large 3
That is its strongest area.
An enterprise with regional data-residency rules
→ GPT-5.4 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-5.4: where it fits
OpenAI's 2026 workhorse — unifies Codex and GPT into a strong default that costs half of GPT-5.5. Released March 5, 2026 by OpenAI, it is built for strong general-purpose default, coding and software engineering, document understanding and tool use, and 1M context with good token efficiency.
Its trade-offs are real: topped by GPT-5.5 on the hardest tasks, and pricier than open-weight rivals. At $2.5 in / $15 out per million tokens, it sits in the mid price band.
Mistral Large 3: where it fits
France's frontier contender — strong multilingual model with European data residency. Released February 2026 by Mistral, it is built for european data-residency option, strong multilingual performance, efficient inference, and function calling.
Its trade-offs: smaller context than US/China frontier, and less benchmark coverage. At $2 in / $6 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
This is less "which is smarter" and more "which ecosystem fits." GPT-5.4 (US) and Mistral Large 3 (France) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Mistral Large 3 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 GPT-5.4 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.
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-5.4 leans toward strong general-purpose default while Mistral Large 3 leans toward european data-residency option, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-5.4 or Mistral Large 3?
Mistral Large 3 is cheaper — $2.5/$15 per 1M tokens vs $2/$6 per 1M tokens, roughly 1.3× apart on input.
Which has the bigger context window?
GPT-5.4 — 1M vs 256K, about 3.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GPT-5.4 and Mistral Large 3 together?
Yes — a multi-model platform like LumiChats gives you GPT-5.4, 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-5.4 or Mistral Large 3?
GPT-5.4 — released March 5, 2026, about 32 days after Mistral Large 3.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.