Both are Mistral AI models. Mistral Small 3.2 24B is the newer, generally stronger default; reach for Mistral Medium 3 when a specific cost or latency profile matters more than the latest capabilities.
Mistral Medium 3 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 is mistral's mid-tier model at $0.40/$2.00 — efficient general capability with a 128K window, below the 1M-context frontier tier. 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 5.3× cheaper on input ($0.075/$0.2 per 1M tokens vs $0.4/$2 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
Context window: Mistral Small 3.2 24B holds 2× more — 256K (~384 pages) vs 128K (~192 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 Small 3.2 24B is the newer model by about 44 days (released June 20, 2025), usually meaning fresher training data and capabilities.
Specifications
Spec
Mistral Medium 3
Mistral Small 3.2 24B
Provider
Mistral AI (France)
Mistral AI (France)
Released
May 7, 2025
June 20, 2025
Context window
128K (~192 pages)
256K (~384 pages)
Price (in/out)
$0.4/$2 per 1M tokens
$0.075/$0.2 per 1M tokens
Open weight?
No — API only
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 cost-to-capability at $0.40/$2.00: Mistral Medium 3 — Mistral Medium 3 lists strong cost-to-capability at $0.40/$2.00 among its strengths; Mistral Small 3.2 24B does not.
General reasoning, coding and multimodal tasks: Mistral Medium 3 — Mistral Medium 3 lists general reasoning, coding and multimodal tasks among its strengths; Mistral Small 3.2 24B does not.
Efficient mid-tier deployment for production workloads: Mistral Medium 3 — Mistral Medium 3 lists efficient mid-tier deployment for production workloads among its strengths; Mistral Small 3.2 24B does not.
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 ($0.4/$2 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 — Its 256K window holds about 2× more than Mistral Medium 3's 128K in a single prompt.
Instruction following and function calling at 24B scale: 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.
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.
Largest single-prompt input: Mistral Small 3.2 24B — Its 256K window is about 2× larger than Mistral Medium 3's 128K, fitting roughly 384 pages in one prompt.
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, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Mistral Small 3.2 24B — Larger 256K window fits more in one prompt.
A team with data-privacy or self-hosting needs: Mistral Small 3.2 24B — Open weights let you run it on your own hardware; Mistral Medium 3 is API-only.
Anyone whose priority is strong cost-to-capability at $0.40/$2.00: Mistral Medium 3 — 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: where it fits
Mistral's mid-tier model at $0.40/$2.00 — efficient general capability with a 128K window, below the 1M-context frontier tier. Released May 7, 2025 by Mistral AI, it is built for strong cost-to-capability at $0.40/$2.00, general reasoning, coding and multimodal tasks, efficient mid-tier deployment for production workloads, and text and image input.
Its trade-offs are real: a 128K context — smaller than the 1M-window flagships here, no published SWE-Bench Verified score, a mid-tier model, not a frontier reasoner, and proprietary, unlike Mistral's open-weight releases. At $0.4 in / $2 out per million tokens, it sits in the budget 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 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 Small 3.2 24B 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 Small 3.2 24B and drop down only with a concrete reason.
Frequently asked questions
Is Mistral Medium 3 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 leans toward strong cost-to-capability at $0.40/$2.00 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 or Mistral Small 3.2 24B?
Mistral Small 3.2 24B is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Mistral Medium 3 is API-metered at $0.4/$2 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?
Mistral Small 3.2 24B — 256K vs 128K, about 2× larger. Useful only if the model actually reasons over the full window, which not all do.
Should I upgrade from Mistral Medium 3 to Mistral Small 3.2 24B?
Since both are Mistral AI models, the newer one (Mistral Small 3.2 24B) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, Mistral Medium 3 or Mistral Small 3.2 24B?
Mistral Small 3.2 24B — released June 20, 2025, about 44 days after Mistral Medium 3.
Mistral Medium 3 vs Mistral Small 3.2 24B
Mistral AI · France | Mistral AI · France · Updated June 2026
Quick verdict
Both are Mistral AI models. Mistral Small 3.2 24B is the newer, generally stronger default; reach for Mistral Medium 3 when a specific cost or latency profile matters more than the latest capabilities.
Mistral Medium 3 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 is mistral's mid-tier model at $0.40/$2.00 — efficient general capability with a 128K window, below the 1M-context frontier tier. 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 5.3× cheaper on input ($0.075/$0.2 per 1M tokens vs $0.4/$2 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
▸Context window: Mistral Small 3.2 24B holds 2× more — 256K (~384 pages) vs 128K (~192 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 Small 3.2 24B is the newer model by about 44 days (released June 20, 2025), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Mistral Medium 3
Mistral Small 3.2 24B
Provider
Mistral AI (France)
Mistral AI (France)
Released
May 7, 2025
June 20, 2025
Context window
128K (~192 pages)
256K (~384 pages)
Price (in/out)
$0.4/$2 per 1M tokens
$0.075/$0.2 per 1M tokens
Open weight?
No — API only
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 cost-to-capability at $0.40/$2.00
Mistral Medium 3
Mistral Medium 3 lists strong cost-to-capability at $0.40/$2.00 among its strengths; Mistral Small 3.2 24B does not.
General reasoning, coding and multimodal tasks
Mistral Medium 3
Mistral Medium 3 lists general reasoning, coding and multimodal tasks among its strengths; Mistral Small 3.2 24B does not.
Efficient mid-tier deployment for production workloads
Mistral Medium 3
Mistral Medium 3 lists efficient mid-tier deployment for production workloads among its strengths; Mistral Small 3.2 24B does not.
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 ($0.4/$2 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
Its 256K window holds about 2× more than Mistral Medium 3's 128K in a single prompt.
Instruction following and function calling at 24B scale
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.
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.
Largest single-prompt input
Mistral Small 3.2 24B
Its 256K window is about 2× larger than Mistral Medium 3's 128K, fitting roughly 384 pages in one prompt.
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, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Mistral Small 3.2 24B
Larger 256K window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ Mistral Small 3.2 24B
Open weights let you run it on your own hardware; Mistral Medium 3 is API-only.
Anyone whose priority is strong cost-to-capability at $0.40/$2.00
→ Mistral Medium 3
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: where it fits
Mistral's mid-tier model at $0.40/$2.00 — efficient general capability with a 128K window, below the 1M-context frontier tier. Released May 7, 2025 by Mistral AI, it is built for strong cost-to-capability at $0.40/$2.00, general reasoning, coding and multimodal tasks, efficient mid-tier deployment for production workloads, and text and image input.
Its trade-offs are real: a 128K context — smaller than the 1M-window flagships here, no published SWE-Bench Verified score, a mid-tier model, not a frontier reasoner, and proprietary, unlike Mistral's open-weight releases. At $0.4 in / $2 out per million tokens, it sits in the budget 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 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 Small 3.2 24B 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 Small 3.2 24B and drop down only with a concrete reason.
Want both Mistral Medium 3 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 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 leans toward strong cost-to-capability at $0.40/$2.00 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 or Mistral Small 3.2 24B?
Mistral Small 3.2 24B is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Mistral Medium 3 is API-metered at $0.4/$2 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?
Mistral Small 3.2 24B — 256K vs 128K, about 2× larger. Useful only if the model actually reasons over the full window, which not all do.
Should I upgrade from Mistral Medium 3 to Mistral Small 3.2 24B?
Since both are Mistral AI models, the newer one (Mistral Small 3.2 24B) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, Mistral Medium 3 or Mistral Small 3.2 24B?
Mistral Small 3.2 24B — released June 20, 2025, about 44 days after Mistral Medium 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.