Both are Mistral AI models. Mistral Medium 3.5 is the newer, generally stronger default; reach for Mistral Small 3.2 24B when its lower price or a specific cost or latency profile matters more than the latest capabilities.
Mistral Medium 3.5 and Mistral Small 3.2 24B are both Mistral AI models, so the real question is not which lab to trust but which tier fits your workload and budget. 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). Mistral Small 3.2 24B is mistral's Apache-2.0 open 24B model at about $0.075/$0.20 hosted — very cheap and self-hostable, sized for volume over frontier quality. Since both come from the same lab, the comparison below focuses on the tier-and-cost trade-offs that actually separate them.
Key differences
Price: Mistral Small 3.2 24B is about 20× cheaper on input ($0.075/$0.2 per 1M tokens vs $1.5/$7.5 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
Context window: both advertise 256K (~384 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
Recency: Mistral Medium 3.5 is the newer model by about 10 months (released April 29, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Mistral Medium 3.5
Mistral Small 3.2 24B
Provider
Mistral AI (France)
Mistral AI (France)
Released
April 29, 2026
June 20, 2025
Context window
256K (~384 pages)
256K (~384 pages)
Price (in/out)
$1.5/$7.5 per 1M tokens
$0.075/$0.2 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, image, code
text, image, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Strong intelligence-for-size — Artificial Analysis Intelligence Index 30, near the top of its price tier: Mistral Medium 3.5 — Mistral Small 3.2 24B is comparatively weak here — hosted prices vary by provider; the figure shown is a common host rate
128B dense open-weight model — self-hostable: Mistral Medium 3.5 — Mistral Small 3.2 24B is comparatively weak here — a 24B small model — not a frontier reasoner
Unifies reasoning and coding into one model with an adjustable reasoning effort: Mistral Medium 3.5 — 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) — and it is the newer of the two.
Extremely cheap open-weight model at about $0.075/$0.20 hosted: Mistral Small 3.2 24B — At $0.075/$0.2 per 1M tokens it undercuts Mistral Medium 3.5 ($1.5/$7.5 per 1M tokens), and that gap compounds at volume.
Self-hostable under Apache-2.0 with no per-token cost: Mistral Small 3.2 24B — Mistral's Apache-2.0 open 24B model at about $0.075/$0.20 hosted — very cheap and self-hostable, sized for volume over frontier quality — and it runs cheaper at $0.075/$0.2 per 1M tokens.
Instruction following and function calling at 24B scale: Mistral Small 3.2 24B — Mistral Small 3.2 24B lists instruction following and function calling at 24B scale among its strengths; Mistral Medium 3.5 does not.
Lowest cost at scale: Mistral Small 3.2 24B — At $0.075/$0.2 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 Small 3.2 24B — At $0.075/$0.2 per 1M tokens it undercuts Mistral Medium 3.5, and on millions of tokens that margin decides the monthly bill.
Anyone whose priority is strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier: Mistral Medium 3.5 — It is specifically built for that.
Anyone whose priority is extremely cheap open-weight model at about $0.075/$0.20 hosted: Mistral Small 3.2 24B — That is its strongest area.
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 are real: 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.
Mistral Small 3.2 24B: where it fits
Mistral's Apache-2.0 open 24B model at about $0.075/$0.20 hosted — very cheap and self-hostable, sized for volume over frontier quality. Released June 20, 2025 by Mistral AI, it is built for extremely cheap open-weight model at about $0.075/$0.20 hosted, self-hostable under Apache-2.0 with no per-token cost, instruction following and function calling at 24B scale, and runs on modest hardware for local or private deployment.
Its trade-offs: a 24B small model — not a frontier reasoner, context reported as 256K but some references cite 128K native, no published SWE-Bench Verified score, and hosted prices vary by provider; the figure shown is a common host rate. At $0.075 in / $0.2 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Because Mistral Medium 3.5 and Mistral Small 3.2 24B come from the same lab (Mistral AI), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. Mistral Medium 3.5 is the more capable, more recent option; the other earns its place only when its price or latency profile fits a specific job better. Most teams should default to Mistral Medium 3.5 and drop down only with a concrete reason.
Frequently asked questions
Is Mistral Medium 3.5 or Mistral Small 3.2 24B 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, Mistral Medium 3.5 leans toward strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier while Mistral Small 3.2 24B leans toward extremely cheap open-weight model at about $0.075/$0.20 hosted, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Mistral Medium 3.5 or Mistral Small 3.2 24B?
Mistral Small 3.2 24B is cheaper — $1.5/$7.5 per 1M tokens vs $0.075/$0.2 per 1M tokens, roughly 20× apart on input.
Which has the bigger context window?
Both advertise 256K (~384 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Should I upgrade from Mistral Small 3.2 24B to Mistral Medium 3.5?
Since both are Mistral AI models, the newer one (Mistral Medium 3.5) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, Mistral Medium 3.5 or Mistral Small 3.2 24B?
Mistral Medium 3.5 — released April 29, 2026, about 10 months after Mistral Small 3.2 24B.
Mistral Medium 3.5 vs Mistral Small 3.2 24B
Mistral AI · France | Mistral AI · France · Updated June 2026
Quick verdict
Both are Mistral AI models. Mistral Medium 3.5 is the newer, generally stronger default; reach for Mistral Small 3.2 24B when its lower price or a specific cost or latency profile matters more than the latest capabilities.
Mistral Medium 3.5 and Mistral Small 3.2 24B are both Mistral AI models, so the real question is not which lab to trust but which tier fits your workload and budget. 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). Mistral Small 3.2 24B is mistral's Apache-2.0 open 24B model at about $0.075/$0.20 hosted — very cheap and self-hostable, sized for volume over frontier quality. Since both come from the same lab, the comparison below focuses on the tier-and-cost trade-offs that actually separate them.
Key differences at a glance
▸Price: Mistral Small 3.2 24B is about 20× cheaper on input ($0.075/$0.2 per 1M tokens vs $1.5/$7.5 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
▸Context window: both advertise 256K (~384 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
▸Recency: Mistral Medium 3.5 is the newer model by about 10 months (released April 29, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Mistral Medium 3.5
Mistral Small 3.2 24B
Provider
Mistral AI (France)
Mistral AI (France)
Released
April 29, 2026
June 20, 2025
Context window
256K (~384 pages)
256K (~384 pages)
Price (in/out)
$1.5/$7.5 per 1M tokens
$0.075/$0.2 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, image, code
text, image, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Strong intelligence-for-size — Artificial Analysis Intelligence Index 30, near the top of its price tier
Mistral Medium 3.5
Mistral Small 3.2 24B is comparatively weak here — hosted prices vary by provider; the figure shown is a common host rate
128B dense open-weight model — self-hostable
Mistral Medium 3.5
Mistral Small 3.2 24B is comparatively weak here — a 24B small model — not a frontier reasoner
Unifies reasoning and coding into one model with an adjustable reasoning effort
Mistral Medium 3.5
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) — and it is the newer of the two.
Extremely cheap open-weight model at about $0.075/$0.20 hosted
Mistral Small 3.2 24B
At $0.075/$0.2 per 1M tokens it undercuts Mistral Medium 3.5 ($1.5/$7.5 per 1M tokens), and that gap compounds at volume.
Self-hostable under Apache-2.0 with no per-token cost
Mistral Small 3.2 24B
Mistral's Apache-2.0 open 24B model at about $0.075/$0.20 hosted — very cheap and self-hostable, sized for volume over frontier quality — and it runs cheaper at $0.075/$0.2 per 1M tokens.
Instruction following and function calling at 24B scale
Mistral Small 3.2 24B
Mistral Small 3.2 24B lists instruction following and function calling at 24B scale among its strengths; Mistral Medium 3.5 does not.
Lowest cost at scale
Mistral Small 3.2 24B
At $0.075/$0.2 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 Small 3.2 24B
At $0.075/$0.2 per 1M tokens it undercuts Mistral Medium 3.5, and on millions of tokens that margin decides the monthly bill.
Anyone whose priority is strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier
→ Mistral Medium 3.5
It is specifically built for that.
Anyone whose priority is extremely cheap open-weight model at about $0.075/$0.20 hosted
→ Mistral Small 3.2 24B
That is its strongest area.
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 are real: 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.
Mistral Small 3.2 24B: where it fits
Mistral's Apache-2.0 open 24B model at about $0.075/$0.20 hosted — very cheap and self-hostable, sized for volume over frontier quality. Released June 20, 2025 by Mistral AI, it is built for extremely cheap open-weight model at about $0.075/$0.20 hosted, self-hostable under Apache-2.0 with no per-token cost, instruction following and function calling at 24B scale, and runs on modest hardware for local or private deployment.
Its trade-offs: a 24B small model — not a frontier reasoner, context reported as 256K but some references cite 128K native, no published SWE-Bench Verified score, and hosted prices vary by provider; the figure shown is a common host rate. At $0.075 in / $0.2 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Because Mistral Medium 3.5 and Mistral Small 3.2 24B come from the same lab (Mistral AI), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. Mistral Medium 3.5 is the more capable, more recent option; the other earns its place only when its price or latency profile fits a specific job better. Most teams should default to Mistral Medium 3.5 and drop down only with a concrete reason.
Want both Mistral Medium 3.5 and Mistral Small 3.2 24B 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 Mistral Medium 3.5 or Mistral Small 3.2 24B 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, Mistral Medium 3.5 leans toward strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier while Mistral Small 3.2 24B leans toward extremely cheap open-weight model at about $0.075/$0.20 hosted, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Mistral Medium 3.5 or Mistral Small 3.2 24B?
Mistral Small 3.2 24B is cheaper — $1.5/$7.5 per 1M tokens vs $0.075/$0.2 per 1M tokens, roughly 20× apart on input.
Which has the bigger context window?
Both advertise 256K (~384 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Should I upgrade from Mistral Small 3.2 24B to Mistral Medium 3.5?
Since both are Mistral AI models, the newer one (Mistral Medium 3.5) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, Mistral Medium 3.5 or Mistral Small 3.2 24B?
Mistral Medium 3.5 — released April 29, 2026, about 10 months after Mistral Small 3.2 24B.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.