Pick Gemma 4 for self-hosted, data-private deployment or running locally or on edge devices. Pick Mistral Small 3.2 24B for extremely cheap open-weight model at about $0.075/$0.20 hosted or self-hostable under apache-2.0 with no per-token cost. On a tight budget at scale, Gemma 4 is the value pick.
Gemma 4 (Google, US) and Mistral Small 3.2 24B (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. Gemma 4 is google's open-weight family: Apache 2.0 licensed, multimodal, and sized from edge devices up, for private self-hosting. 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. Their biggest split is price, and the breakdown below shows exactly how that plays out for your workload.
Key differences
Context window: both advertise 256K (~384 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
Recency: Gemma 4 is the newer model by about 10 months (released April 2, 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
Gemma 4
Mistral Small 3.2 24B
Provider
Google (US)
Mistral AI (France)
Released
April 2, 2026
June 20, 2025
Context window
256K (~384 pages)
256K (~384 pages)
Price (in/out)
Open weight (self-host / free)
$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
Self-hosted, data-private deployment: Gemma 4 — Mistral Small 3.2 24B is comparatively weak here — hosted prices vary by provider; the figure shown is a common host rate
Running locally or on edge devices: Gemma 4 — Google's open-weight family: Apache 2.0 licensed, multimodal, and sized from edge devices up, for private self-hosting — and it is the newer of the two.
Fine-tuning on your own data: Gemma 4 — Gemma 4 lists fine-tuning on your own data 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 — Gemma 4 is comparatively weak here — trails frontier closed models on the hardest tasks
Self-hostable under Apache-2.0 with no per-token cost: Mistral Small 3.2 24B — Mistral Small 3.2 24B lists self-hostable under Apache-2.0 with no per-token cost among its strengths; Gemma 4 does not.
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; Gemma 4 does not.
Lowest cost at scale: Gemma 4 — Its weights are open, so at volume you pay for your own hardware instead of Mistral Small 3.2 24B's $0.075/$0.2 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume: Gemma 4 — At Open weight (self-host / free) it undercuts Mistral Small 3.2 24B, and on millions of tokens that margin decides the monthly bill.
Anyone whose priority is self-hosted, data-private deployment: Gemma 4 — 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.
An enterprise with regional data-residency rules: Gemma 4 or Mistral Small 3.2 24B — Origin (US vs France) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
Gemma 4: where it fits
Google's open-weight family: Apache 2.0 licensed, multimodal, and sized from edge devices up, for private self-hosting. Released April 2, 2026 by Google, it is built for self-hosted, data-private deployment, running locally or on edge devices, fine-tuning on your own data, and multimodal tasks over a 256K context.
Its trade-offs are real: trails frontier closed models on the hardest tasks, and needs your own hardware to run. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
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
This is less "which is smarter" and more "which ecosystem fits." Gemma 4 (US) and Mistral Small 3.2 24B (France) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Gemma 4 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 Gemma 4 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, Gemma 4 leans toward self-hosted, data-private deployment 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, Gemma 4 or Mistral Small 3.2 24B?
Gemma 4 is cheaper — Open weight (self-host / free) vs $0.075/$0.2 per 1M tokens.
Which has the bigger context window?
Both advertise 256K (~384 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Gemma 4 and Mistral Small 3.2 24B together?
Yes — a multi-model platform like LumiChats gives you Gemma 4, Mistral Small 3.2 24B 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, Gemma 4 or Mistral Small 3.2 24B?
Gemma 4 — released April 2, 2026, about 10 months after Mistral Small 3.2 24B.
Gemma 4 vs Mistral Small 3.2 24B
Google · US | Mistral AI · France · Updated June 2026
Quick verdict
Pick Gemma 4 for self-hosted, data-private deployment or running locally or on edge devices. Pick Mistral Small 3.2 24B for extremely cheap open-weight model at about $0.075/$0.20 hosted or self-hostable under apache-2.0 with no per-token cost. On a tight budget at scale, Gemma 4 is the value pick.
Gemma 4 (Google, US) and Mistral Small 3.2 24B (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. Gemma 4 is google's open-weight family: Apache 2.0 licensed, multimodal, and sized from edge devices up, for private self-hosting. 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. Their biggest split is price, and the breakdown below shows exactly how that plays out for your workload.
Key differences at a glance
▸Context window: both advertise 256K (~384 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
▸Recency: Gemma 4 is the newer model by about 10 months (released April 2, 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
Gemma 4
Mistral Small 3.2 24B
Provider
Google (US)
Mistral AI (France)
Released
April 2, 2026
June 20, 2025
Context window
256K (~384 pages)
256K (~384 pages)
Price (in/out)
Open weight (self-host / free)
$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
Self-hosted, data-private deployment
Gemma 4
Mistral Small 3.2 24B is comparatively weak here — hosted prices vary by provider; the figure shown is a common host rate
Running locally or on edge devices
Gemma 4
Google's open-weight family: Apache 2.0 licensed, multimodal, and sized from edge devices up, for private self-hosting — and it is the newer of the two.
Fine-tuning on your own data
Gemma 4
Gemma 4 lists fine-tuning on your own data 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
Gemma 4 is comparatively weak here — trails frontier closed models on the hardest tasks
Self-hostable under Apache-2.0 with no per-token cost
Mistral Small 3.2 24B
Mistral Small 3.2 24B lists self-hostable under Apache-2.0 with no per-token cost among its strengths; Gemma 4 does not.
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; Gemma 4 does not.
Lowest cost at scale
Gemma 4
Its weights are open, so at volume you pay for your own hardware instead of Mistral Small 3.2 24B's $0.075/$0.2 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Gemma 4
At Open weight (self-host / free) it undercuts Mistral Small 3.2 24B, and on millions of tokens that margin decides the monthly bill.
Anyone whose priority is self-hosted, data-private deployment
→ Gemma 4
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.
An enterprise with regional data-residency rules
→ Gemma 4 or Mistral Small 3.2 24B
Origin (US vs France) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
Gemma 4: where it fits
Google's open-weight family: Apache 2.0 licensed, multimodal, and sized from edge devices up, for private self-hosting. Released April 2, 2026 by Google, it is built for self-hosted, data-private deployment, running locally or on edge devices, fine-tuning on your own data, and multimodal tasks over a 256K context.
Its trade-offs are real: trails frontier closed models on the hardest tasks, and needs your own hardware to run. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
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
This is less "which is smarter" and more "which ecosystem fits." Gemma 4 (US) and Mistral Small 3.2 24B (France) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Gemma 4 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 Gemma 4 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 Gemma 4 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, Gemma 4 leans toward self-hosted, data-private deployment 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, Gemma 4 or Mistral Small 3.2 24B?
Gemma 4 is cheaper — Open weight (self-host / free) vs $0.075/$0.2 per 1M tokens.
Which has the bigger context window?
Both advertise 256K (~384 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Gemma 4 and Mistral Small 3.2 24B together?
Yes — a multi-model platform like LumiChats gives you Gemma 4, Mistral Small 3.2 24B 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, Gemma 4 or Mistral Small 3.2 24B?
Gemma 4 — released April 2, 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.