Pick GPT-5.3-Codex for dedicated coding agent or cli and ide integration. Pick Mistral Medium 3.5 for strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier or 128b dense open-weight model — self-hostable. Choose Mistral Medium 3.5 if you need self-hosting or data privacy; GPT-5.3-Codex if you want a managed API.
GPT-5.3-Codex (OpenAI, US) and Mistral Medium 3.5 (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. GPT-5.3-Codex is openAI's coding-specialized agent model for autonomous software engineering. Mistral Medium 3.5 is mistral's efficient 128B open-weight model — a single dense model unifying reasoning and coding that punches above its size on independent tests (AA Index 30). They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Price: nearly identical — $1.75/$14 per 1M tokens vs $1.5/$7.5 per 1M tokens. Cost will not be the deciding factor here.
Context window: GPT-5.3-Codex holds 1.6× more — 400K (~600 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: Mistral Medium 3.5 is the newer model by about 2 months (released April 29, 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-5.3-Codex
Mistral Medium 3.5
Provider
OpenAI (US)
Mistral AI (France)
Released
February 24, 2026
April 29, 2026
Context window
400K (~600 pages)
256K (~384 pages)
Price (in/out)
$1.75/$14 per 1M tokens
$1.5/$7.5 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, code
text, image, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Dedicated coding agent: GPT-5.3-Codex — OpenAI's coding-specialized agent model for autonomous software engineering — and it carries the larger 400K context.
CLI and IDE integration: GPT-5.3-Codex — GPT-5.3-Codex lists cLI and IDE integration among its strengths; Mistral Medium 3.5 does not.
Autonomous software tasks: GPT-5.3-Codex — GPT-5.3-Codex lists autonomous software tasks among its strengths; Mistral Medium 3.5 does not.
Strong intelligence-for-size — Artificial Analysis Intelligence Index 30, near the top of its price tier: Mistral Medium 3.5 — At $1.5/$7.5 per 1M tokens it undercuts GPT-5.3-Codex ($1.75/$14 per 1M tokens), and that gap compounds at volume.
128B dense open-weight model — self-hostable: Mistral Medium 3.5 — Open weights make this possible at all — GPT-5.3-Codex is API-only, so it cannot leave the vendor's servers.
Unifies reasoning and coding into one model with an adjustable reasoning effort: Mistral Medium 3.5 — GPT-5.3-Codex is comparatively weak here — coding-specialized, narrower general use
Lowest cost at scale: Mistral Medium 3.5 — At $1.5/$7.5 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: GPT-5.3-Codex — Its 400K window is about 1.6× larger than Mistral Medium 3.5's 256K, fitting roughly 600 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Mistral Medium 3.5 — At $1.5/$7.5 per 1M tokens it undercuts GPT-5.3-Codex, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: GPT-5.3-Codex — Larger 400K window fits more in one prompt.
A team with data-privacy or self-hosting needs: Mistral Medium 3.5 — Open weights let you run it on your own hardware; GPT-5.3-Codex is API-only.
Anyone whose priority is dedicated coding agent: GPT-5.3-Codex — It is specifically built for that.
Anyone whose priority is strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier: Mistral Medium 3.5 — That is its strongest area.
An enterprise with regional data-residency rules: GPT-5.3-Codex or Mistral Medium 3.5 — Origin (US vs France) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
GPT-5.3-Codex: where it fits
OpenAI's coding-specialized agent model for autonomous software engineering. Released February 24, 2026 by OpenAI, it is built for dedicated coding agent, cLI and IDE integration, autonomous software tasks, and tool calling.
Its trade-offs are real: coding-specialized, narrower general use, and retired in favor of GPT-5.5 Codex. At $1.75 in / $14 out per million tokens, it sits in the mid price band.
Mistral Medium 3.5: where it fits
Mistral's efficient 128B open-weight model — a single dense model unifying reasoning and coding that punches above its size on independent tests (AA Index 30). Released April 29, 2026 by Mistral AI, it is built for strong intelligence-for-size — Artificial Analysis Intelligence Index 30, near the top of its price tier, 128B dense open-weight model — self-hostable, unifies reasoning and coding into one model with an adjustable reasoning effort, and 256K context with text and image input.
Its trade-offs: below the absolute frontier — a value/efficiency pick, not a flagship-beater, output pricing ($7.50/M) is higher than the cheapest Chinese rivals, license framing ('open' vs enterprise) varies across sources — confirm terms for commercial use, and no native video or audio. At $1.5 in / $7.5 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
The defining split here is open vs. closed. Mistral Medium 3.5 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. GPT-5.3-Codex 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.
Frequently asked questions
Is GPT-5.3-Codex or Mistral Medium 3.5 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-5.3-Codex leans toward dedicated coding agent while Mistral Medium 3.5 leans toward strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-5.3-Codex or Mistral Medium 3.5?
Mistral Medium 3.5 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while GPT-5.3-Codex is API-metered at $1.75/$14 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-5.3-Codex — 400K vs 256K, about 1.6× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GPT-5.3-Codex and Mistral Medium 3.5 together?
Yes — a multi-model platform like LumiChats gives you GPT-5.3-Codex, Mistral Medium 3.5 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-5.3-Codex or Mistral Medium 3.5?
Mistral Medium 3.5 — released April 29, 2026, about 2 months after GPT-5.3-Codex.
GPT-5.3-Codex vs Mistral Medium 3.5
OpenAI · US | Mistral AI · France · Updated June 2026
Quick verdict
Pick GPT-5.3-Codex for dedicated coding agent or cli and ide integration. Pick Mistral Medium 3.5 for strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier or 128b dense open-weight model — self-hostable. Choose Mistral Medium 3.5 if you need self-hosting or data privacy; GPT-5.3-Codex if you want a managed API.
GPT-5.3-Codex (OpenAI, US) and Mistral Medium 3.5 (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. GPT-5.3-Codex is openAI's coding-specialized agent model for autonomous software engineering. Mistral Medium 3.5 is mistral's efficient 128B open-weight model — a single dense model unifying reasoning and coding that punches above its size on independent tests (AA Index 30). 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
▸Price: nearly identical — $1.75/$14 per 1M tokens vs $1.5/$7.5 per 1M tokens. Cost will not be the deciding factor here.
▸Context window: GPT-5.3-Codex holds 1.6× more — 400K (~600 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: Mistral Medium 3.5 is the newer model by about 2 months (released April 29, 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-5.3-Codex
Mistral Medium 3.5
Provider
OpenAI (US)
Mistral AI (France)
Released
February 24, 2026
April 29, 2026
Context window
400K (~600 pages)
256K (~384 pages)
Price (in/out)
$1.75/$14 per 1M tokens
$1.5/$7.5 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, code
text, image, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Dedicated coding agent
GPT-5.3-Codex
OpenAI's coding-specialized agent model for autonomous software engineering — and it carries the larger 400K context.
CLI and IDE integration
GPT-5.3-Codex
GPT-5.3-Codex lists cLI and IDE integration among its strengths; Mistral Medium 3.5 does not.
Autonomous software tasks
GPT-5.3-Codex
GPT-5.3-Codex lists autonomous software tasks among its strengths; Mistral Medium 3.5 does not.
Strong intelligence-for-size — Artificial Analysis Intelligence Index 30, near the top of its price tier
Mistral Medium 3.5
At $1.5/$7.5 per 1M tokens it undercuts GPT-5.3-Codex ($1.75/$14 per 1M tokens), and that gap compounds at volume.
128B dense open-weight model — self-hostable
Mistral Medium 3.5
Open weights make this possible at all — GPT-5.3-Codex is API-only, so it cannot leave the vendor's servers.
Unifies reasoning and coding into one model with an adjustable reasoning effort
Mistral Medium 3.5
GPT-5.3-Codex is comparatively weak here — coding-specialized, narrower general use
Lowest cost at scale
Mistral Medium 3.5
At $1.5/$7.5 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
GPT-5.3-Codex
Its 400K window is about 1.6× larger than Mistral Medium 3.5's 256K, fitting roughly 600 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Mistral Medium 3.5
At $1.5/$7.5 per 1M tokens it undercuts GPT-5.3-Codex, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ GPT-5.3-Codex
Larger 400K window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ Mistral Medium 3.5
Open weights let you run it on your own hardware; GPT-5.3-Codex is API-only.
Anyone whose priority is dedicated coding agent
→ GPT-5.3-Codex
It is specifically built for that.
Anyone whose priority is strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier
→ Mistral Medium 3.5
That is its strongest area.
An enterprise with regional data-residency rules
→ GPT-5.3-Codex or Mistral Medium 3.5
Origin (US vs France) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
GPT-5.3-Codex: where it fits
OpenAI's coding-specialized agent model for autonomous software engineering. Released February 24, 2026 by OpenAI, it is built for dedicated coding agent, cLI and IDE integration, autonomous software tasks, and tool calling.
Its trade-offs are real: coding-specialized, narrower general use, and retired in favor of GPT-5.5 Codex. At $1.75 in / $14 out per million tokens, it sits in the mid price band.
Mistral Medium 3.5: where it fits
Mistral's efficient 128B open-weight model — a single dense model unifying reasoning and coding that punches above its size on independent tests (AA Index 30). Released April 29, 2026 by Mistral AI, it is built for strong intelligence-for-size — Artificial Analysis Intelligence Index 30, near the top of its price tier, 128B dense open-weight model — self-hostable, unifies reasoning and coding into one model with an adjustable reasoning effort, and 256K context with text and image input.
Its trade-offs: below the absolute frontier — a value/efficiency pick, not a flagship-beater, output pricing ($7.50/M) is higher than the cheapest Chinese rivals, license framing ('open' vs enterprise) varies across sources — confirm terms for commercial use, and no native video or audio. At $1.5 in / $7.5 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
The defining split here is open vs. closed. Mistral Medium 3.5 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. GPT-5.3-Codex 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-5.3-Codex and Mistral Medium 3.5 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.
Is GPT-5.3-Codex or Mistral Medium 3.5 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-5.3-Codex leans toward dedicated coding agent while Mistral Medium 3.5 leans toward strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-5.3-Codex or Mistral Medium 3.5?
Mistral Medium 3.5 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while GPT-5.3-Codex is API-metered at $1.75/$14 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-5.3-Codex — 400K vs 256K, about 1.6× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GPT-5.3-Codex and Mistral Medium 3.5 together?
Yes — a multi-model platform like LumiChats gives you GPT-5.3-Codex, Mistral Medium 3.5 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-5.3-Codex or Mistral Medium 3.5?
Mistral Medium 3.5 — released April 29, 2026, about 2 months after GPT-5.3-Codex.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.