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. Pick North Mini Code for agentic software engineering, code generation, and terminal tasks or efficient sparse moe — 3b active of 30b, runs on a single h100. On a tight budget at scale, North Mini Code is the value pick.
Mistral Small 3.2 24B (Mistral AI) and North Mini Code (Cohere) are two of the models people most often weigh against each other in 2026. 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. North Mini Code is cohere's first agentic coding model: an open-weight 30B/3B-active MoE built for real software-engineering and terminal tasks that runs on a single H100. 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: North Mini Code is the newer model by about 12 months (released June 9, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Mistral Small 3.2 24B
North Mini Code
Provider
Mistral AI (France)
Cohere (Global)
Released
June 20, 2025
June 9, 2026
Context window
256K (~384 pages)
256K (~384 pages)
Price (in/out)
$0.075/$0.2 per 1M tokens
Open weight (self-host / free)
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, image, code
text, code
SWE-Bench Verified
Not published
67.6%
MRCR v2 @ 1M
Not published
Not published
Who wins what
Extremely cheap open-weight model at about $0.075/$0.20 hosted: Mistral Small 3.2 24B — North Mini Code is comparatively weak here — 256K context and modest general-intelligence index trail frontier models
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; North Mini Code 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; North Mini Code does not.
Agentic software engineering, code generation, and terminal tasks: North Mini Code — Cohere's first agentic coding model: an open-weight 30B/3B-active MoE built for real software-engineering and terminal tasks that runs on a single H100 — and it is the newer of the two.
Efficient sparse MoE — 3B active of 30B, runs on a single H100: North Mini Code — North Mini Code lists efficient sparse MoE — 3B active of 30B, runs on a single H100 among its strengths; Mistral Small 3.2 24B does not.
High throughput (up to 2.8x Devstral Small 2) at low latency: North Mini Code — Mistral Small 3.2 24B is comparatively weak here — a 24B small model — not a frontier reasoner
Lowest cost at scale: North Mini Code — 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: North Mini Code — 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 extremely cheap open-weight model at about $0.075/$0.20 hosted: Mistral Small 3.2 24B — It is specifically built for that.
Anyone whose priority is agentic software engineering, code generation, and terminal tasks: North Mini Code — That is its strongest area.
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 are real: 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.
North Mini Code: where it fits
Cohere's first agentic coding model: an open-weight 30B/3B-active MoE built for real software-engineering and terminal tasks that runs on a single H100. Released June 9, 2026 by Cohere, it is built for agentic software engineering, code generation, and terminal tasks, efficient sparse MoE — 3B active of 30B, runs on a single H100, high throughput (up to 2.8x Devstral Small 2) at low latency, and fully open weights under Apache 2.0 with fp8 and 4-bit builds.
Its trade-offs: text-only and coding-specialized — not multimodal or general-purpose, and 256K context and modest general-intelligence index trail frontier models. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
Mistral Small 3.2 24B and North Mini Code overlap enough that the right pick depends on your specific job. North Mini Code costs less per token; and each leads in its own area — Mistral Small 3.2 24B for extremely cheap open-weight model at about $0.075/$0.20 hosted, North Mini Code for agentic software engineering, code generation, and terminal tasks. Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is Mistral Small 3.2 24B or North Mini Code better for coding?
Public SWE-Bench figures are not available for Mistral Small 3.2 24B, so the honest test is your own repository — run an identical real bug through both. By design, Mistral Small 3.2 24B leans toward extremely cheap open-weight model at about $0.075/$0.20 hosted while North Mini Code leans toward agentic software engineering, code generation, and terminal tasks, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Mistral Small 3.2 24B or North Mini Code?
North Mini Code is cheaper — $0.075/$0.2 per 1M tokens vs Open weight (self-host / free).
Which has the bigger context window?
Both advertise 256K (~384 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Mistral Small 3.2 24B and North Mini Code together?
Yes — a multi-model platform like LumiChats gives you Mistral Small 3.2 24B, North Mini Code 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, Mistral Small 3.2 24B or North Mini Code?
North Mini Code — released June 9, 2026, about 12 months after Mistral Small 3.2 24B.
Mistral Small 3.2 24B vs North Mini Code
Mistral AI · France | Cohere · Global · Updated June 2026
Quick verdict
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. Pick North Mini Code for agentic software engineering, code generation, and terminal tasks or efficient sparse moe — 3b active of 30b, runs on a single h100. On a tight budget at scale, North Mini Code is the value pick.
Mistral Small 3.2 24B (Mistral AI) and North Mini Code (Cohere) are two of the models people most often weigh against each other in 2026. 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. North Mini Code is cohere's first agentic coding model: an open-weight 30B/3B-active MoE built for real software-engineering and terminal tasks that runs on a single H100. 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: North Mini Code is the newer model by about 12 months (released June 9, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Mistral Small 3.2 24B
North Mini Code
Provider
Mistral AI (France)
Cohere (Global)
Released
June 20, 2025
June 9, 2026
Context window
256K (~384 pages)
256K (~384 pages)
Price (in/out)
$0.075/$0.2 per 1M tokens
Open weight (self-host / free)
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, image, code
text, code
SWE-Bench Verified
Not published
67.6%
MRCR v2 @ 1M
Not published
Not published
Who wins what
Extremely cheap open-weight model at about $0.075/$0.20 hosted
Mistral Small 3.2 24B
North Mini Code is comparatively weak here — 256K context and modest general-intelligence index trail frontier models
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; North Mini Code 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; North Mini Code does not.
Agentic software engineering, code generation, and terminal tasks
North Mini Code
Cohere's first agentic coding model: an open-weight 30B/3B-active MoE built for real software-engineering and terminal tasks that runs on a single H100 — and it is the newer of the two.
Efficient sparse MoE — 3B active of 30B, runs on a single H100
North Mini Code
North Mini Code lists efficient sparse MoE — 3B active of 30B, runs on a single H100 among its strengths; Mistral Small 3.2 24B does not.
High throughput (up to 2.8x Devstral Small 2) at low latency
North Mini Code
Mistral Small 3.2 24B is comparatively weak here — a 24B small model — not a frontier reasoner
Lowest cost at scale
North Mini Code
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
→ North Mini Code
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 extremely cheap open-weight model at about $0.075/$0.20 hosted
→ Mistral Small 3.2 24B
It is specifically built for that.
Anyone whose priority is agentic software engineering, code generation, and terminal tasks
→ North Mini Code
That is its strongest area.
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 are real: 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.
North Mini Code: where it fits
Cohere's first agentic coding model: an open-weight 30B/3B-active MoE built for real software-engineering and terminal tasks that runs on a single H100. Released June 9, 2026 by Cohere, it is built for agentic software engineering, code generation, and terminal tasks, efficient sparse MoE — 3B active of 30B, runs on a single H100, high throughput (up to 2.8x Devstral Small 2) at low latency, and fully open weights under Apache 2.0 with fp8 and 4-bit builds.
Its trade-offs: text-only and coding-specialized — not multimodal or general-purpose, and 256K context and modest general-intelligence index trail frontier models. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
Mistral Small 3.2 24B and North Mini Code overlap enough that the right pick depends on your specific job. North Mini Code costs less per token; and each leads in its own area — Mistral Small 3.2 24B for extremely cheap open-weight model at about $0.075/$0.20 hosted, North Mini Code for agentic software engineering, code generation, and terminal tasks. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Mistral Small 3.2 24B and North Mini Code 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 Small 3.2 24B or North Mini Code better for coding?
Public SWE-Bench figures are not available for Mistral Small 3.2 24B, so the honest test is your own repository — run an identical real bug through both. By design, Mistral Small 3.2 24B leans toward extremely cheap open-weight model at about $0.075/$0.20 hosted while North Mini Code leans toward agentic software engineering, code generation, and terminal tasks, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Mistral Small 3.2 24B or North Mini Code?
North Mini Code is cheaper — $0.075/$0.2 per 1M tokens vs Open weight (self-host / free).
Which has the bigger context window?
Both advertise 256K (~384 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Mistral Small 3.2 24B and North Mini Code together?
Yes — a multi-model platform like LumiChats gives you Mistral Small 3.2 24B, North Mini Code 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, Mistral Small 3.2 24B or North Mini Code?
North Mini Code — released June 9, 2026, about 12 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.