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 NVIDIA Nemotron 3 Ultra for the most capable open-weight model from a us lab (artificial analysis intelligence index of about 48) or fast, efficient long-horizon agentic reasoning via a hybrid mamba-transformer design. On a tight budget at scale, NVIDIA Nemotron 3 Ultra is the value pick.
Mistral Small 3.2 24B (Mistral AI, France) and NVIDIA Nemotron 3 Ultra (NVIDIA, US) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. 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. NVIDIA Nemotron 3 Ultra is nVIDIA's open-weight reasoning flagship (about 550B total, 55B active) — the most capable open model from a US lab, built for long-running agents. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Context window: NVIDIA Nemotron 3 Ultra holds 3.9× more — 1M (~1,500 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: NVIDIA Nemotron 3 Ultra is the newer model by about 12 months (released June 4, 2026), usually meaning fresher training data and capabilities.
Ecosystem: this is a France-vs-US matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Specifications
Spec
Mistral Small 3.2 24B
NVIDIA Nemotron 3 Ultra
Provider
Mistral AI (France)
NVIDIA (US)
Released
June 20, 2025
June 4, 2026
Context window
256K (~384 pages)
1M (~1,500 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
Not published
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 — NVIDIA Nemotron 3 Ultra is comparatively weak here — trails the best Chinese open models on overall intelligence
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; NVIDIA Nemotron 3 Ultra 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; NVIDIA Nemotron 3 Ultra does not.
The most capable open-weight model from a US lab (Artificial Analysis Intelligence Index of about 48): NVIDIA Nemotron 3 Ultra — Mistral Small 3.2 24B is comparatively weak here — a 24B small model — not a frontier reasoner
Fast, efficient long-horizon agentic reasoning via a hybrid Mamba-Transformer design: NVIDIA Nemotron 3 Ultra — Its 1M window holds about 3.9× more than Mistral Small 3.2 24B's 256K in a single prompt.
A fully open release — weights, training data, and recipes under a permissive license: NVIDIA Nemotron 3 Ultra — NVIDIA's open-weight reasoning flagship (about 550B total, 55B active) — the most capable open model from a US lab, built for long-running agents — and it carries the larger 1M context.
Lowest cost at scale: NVIDIA Nemotron 3 Ultra — 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.
Largest single-prompt input: NVIDIA Nemotron 3 Ultra — Its 1M window is about 3.9× larger than Mistral Small 3.2 24B's 256K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: NVIDIA Nemotron 3 Ultra — At Open weight (self-host / free) it undercuts Mistral Small 3.2 24B, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: NVIDIA Nemotron 3 Ultra — Larger 1M window fits more in one prompt.
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 the most capable open-weight model from a us lab (artificial analysis intelligence index of about 48): NVIDIA Nemotron 3 Ultra — That is its strongest area.
An enterprise with regional data-residency rules: NVIDIA Nemotron 3 Ultra or Mistral Small 3.2 24B — Origin (France vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
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.
NVIDIA Nemotron 3 Ultra: where it fits
NVIDIA's open-weight reasoning flagship (about 550B total, 55B active) — the most capable open model from a US lab, built for long-running agents. Released June 4, 2026 by NVIDIA, it is built for the most capable open-weight model from a US lab (Artificial Analysis Intelligence Index of about 48), fast, efficient long-horizon agentic reasoning via a hybrid Mamba-Transformer design, a fully open release — weights, training data, and recipes under a permissive license, and strong coding for an open model (SWE-Bench Verified in the high 60s).
Its trade-offs: trails the best Chinese open models on overall intelligence, and a 550B mixture-of-experts is heavy to self-host, and the 1M context is rarely served in full. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
This is less "which is smarter" and more "which ecosystem fits." Mistral Small 3.2 24B (France) and NVIDIA Nemotron 3 Ultra (US) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. NVIDIA Nemotron 3 Ultra 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 Mistral Small 3.2 24B or NVIDIA Nemotron 3 Ultra 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 Small 3.2 24B leans toward extremely cheap open-weight model at about $0.075/$0.20 hosted while NVIDIA Nemotron 3 Ultra leans toward the most capable open-weight model from a us lab (artificial analysis intelligence index of about 48), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Mistral Small 3.2 24B or NVIDIA Nemotron 3 Ultra?
NVIDIA Nemotron 3 Ultra is cheaper — $0.075/$0.2 per 1M tokens vs Open weight (self-host / free).
Which has the bigger context window?
NVIDIA Nemotron 3 Ultra — 1M vs 256K, about 3.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Mistral Small 3.2 24B and NVIDIA Nemotron 3 Ultra together?
Yes — a multi-model platform like LumiChats gives you Mistral Small 3.2 24B, NVIDIA Nemotron 3 Ultra 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 NVIDIA Nemotron 3 Ultra?
NVIDIA Nemotron 3 Ultra — released June 4, 2026, about 12 months after Mistral Small 3.2 24B.
Mistral Small 3.2 24B vs NVIDIA Nemotron 3 Ultra
Mistral AI · France | NVIDIA · US · 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 NVIDIA Nemotron 3 Ultra for the most capable open-weight model from a us lab (artificial analysis intelligence index of about 48) or fast, efficient long-horizon agentic reasoning via a hybrid mamba-transformer design. On a tight budget at scale, NVIDIA Nemotron 3 Ultra is the value pick.
Mistral Small 3.2 24B (Mistral AI, France) and NVIDIA Nemotron 3 Ultra (NVIDIA, US) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. 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. NVIDIA Nemotron 3 Ultra is nVIDIA's open-weight reasoning flagship (about 550B total, 55B active) — the most capable open model from a US lab, built for long-running agents. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Context window: NVIDIA Nemotron 3 Ultra holds 3.9× more — 1M (~1,500 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: NVIDIA Nemotron 3 Ultra is the newer model by about 12 months (released June 4, 2026), usually meaning fresher training data and capabilities.
▸Ecosystem: this is a France-vs-US matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
Spec
Mistral Small 3.2 24B
NVIDIA Nemotron 3 Ultra
Provider
Mistral AI (France)
NVIDIA (US)
Released
June 20, 2025
June 4, 2026
Context window
256K (~384 pages)
1M (~1,500 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
Not published
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
NVIDIA Nemotron 3 Ultra is comparatively weak here — trails the best Chinese open models on overall intelligence
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; NVIDIA Nemotron 3 Ultra 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; NVIDIA Nemotron 3 Ultra does not.
The most capable open-weight model from a US lab (Artificial Analysis Intelligence Index of about 48)
NVIDIA Nemotron 3 Ultra
Mistral Small 3.2 24B is comparatively weak here — a 24B small model — not a frontier reasoner
Fast, efficient long-horizon agentic reasoning via a hybrid Mamba-Transformer design
NVIDIA Nemotron 3 Ultra
Its 1M window holds about 3.9× more than Mistral Small 3.2 24B's 256K in a single prompt.
A fully open release — weights, training data, and recipes under a permissive license
NVIDIA Nemotron 3 Ultra
NVIDIA's open-weight reasoning flagship (about 550B total, 55B active) — the most capable open model from a US lab, built for long-running agents — and it carries the larger 1M context.
Lowest cost at scale
NVIDIA Nemotron 3 Ultra
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.
Largest single-prompt input
NVIDIA Nemotron 3 Ultra
Its 1M window is about 3.9× larger than Mistral Small 3.2 24B's 256K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ NVIDIA Nemotron 3 Ultra
At Open weight (self-host / free) it undercuts Mistral Small 3.2 24B, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ NVIDIA Nemotron 3 Ultra
Larger 1M window fits more in one prompt.
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 the most capable open-weight model from a us lab (artificial analysis intelligence index of about 48)
→ NVIDIA Nemotron 3 Ultra
That is its strongest area.
An enterprise with regional data-residency rules
→ NVIDIA Nemotron 3 Ultra or Mistral Small 3.2 24B
Origin (France vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
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.
NVIDIA Nemotron 3 Ultra: where it fits
NVIDIA's open-weight reasoning flagship (about 550B total, 55B active) — the most capable open model from a US lab, built for long-running agents. Released June 4, 2026 by NVIDIA, it is built for the most capable open-weight model from a US lab (Artificial Analysis Intelligence Index of about 48), fast, efficient long-horizon agentic reasoning via a hybrid Mamba-Transformer design, a fully open release — weights, training data, and recipes under a permissive license, and strong coding for an open model (SWE-Bench Verified in the high 60s).
Its trade-offs: trails the best Chinese open models on overall intelligence, and a 550B mixture-of-experts is heavy to self-host, and the 1M context is rarely served in full. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
This is less "which is smarter" and more "which ecosystem fits." Mistral Small 3.2 24B (France) and NVIDIA Nemotron 3 Ultra (US) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. NVIDIA Nemotron 3 Ultra 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 Mistral Small 3.2 24B and NVIDIA Nemotron 3 Ultra 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 NVIDIA Nemotron 3 Ultra 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 Small 3.2 24B leans toward extremely cheap open-weight model at about $0.075/$0.20 hosted while NVIDIA Nemotron 3 Ultra leans toward the most capable open-weight model from a us lab (artificial analysis intelligence index of about 48), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Mistral Small 3.2 24B or NVIDIA Nemotron 3 Ultra?
NVIDIA Nemotron 3 Ultra is cheaper — $0.075/$0.2 per 1M tokens vs Open weight (self-host / free).
Which has the bigger context window?
NVIDIA Nemotron 3 Ultra — 1M vs 256K, about 3.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Mistral Small 3.2 24B and NVIDIA Nemotron 3 Ultra together?
Yes — a multi-model platform like LumiChats gives you Mistral Small 3.2 24B, NVIDIA Nemotron 3 Ultra 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 NVIDIA Nemotron 3 Ultra?
NVIDIA Nemotron 3 Ultra — released June 4, 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.