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. Pick OLMo 3 32B Think for the most fully transparent open release available - ai2 publishes the complete weights, full dolma training dataset, every training checkpoint, training logs, and pretraining/instruction-tuning/rl code, not just final weights or a genuine 32b reasoning ('think') model that generates explicit chain-of-thought.
NVIDIA Nemotron 3 Ultra (NVIDIA) and OLMo 3 32B Think (Allen Institute for AI) are two of the models people most often weigh against each other in 2026. 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. OLMo 3 32B Think is allen Institute for AI's fully-open 32B reasoning model - the rare release that ships the complete training data and process, not just the weights. Their biggest split is context window, and the breakdown below shows exactly how that plays out for your workload.
Key differences
Context window: NVIDIA Nemotron 3 Ultra holds 15× more — 1M (~1,500 pages) vs 65K (~98 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 7 months (released June 4, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
NVIDIA Nemotron 3 Ultra
OLMo 3 32B Think
Provider
NVIDIA (US)
Allen Institute for AI (US)
Released
June 4, 2026
November 20, 2025
Context window
1M (~1,500 pages)
65K (~98 pages)
Price (in/out)
Open weight (self-host / free)
Open weight (self-host / free)
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
The most capable open-weight model from a US lab (Artificial Analysis Intelligence Index of about 48): NVIDIA Nemotron 3 Ultra — OLMo 3 32B Think is comparatively weak here — a 65K context window is modest next to million-token frontier models
Fast, efficient long-horizon agentic reasoning via a hybrid Mamba-Transformer design: NVIDIA Nemotron 3 Ultra — Its 1M window holds about 15× more than OLMo 3 32B Think's 65K 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.
The most fully transparent open release available - Ai2 publishes the complete weights, full Dolma training dataset, every training checkpoint, training logs, and pretraining/instruction-tuning/RL code, not just final weights: OLMo 3 32B Think — OLMo 3 32B Think lists the most fully transparent open release available - Ai2 publishes the complete weights, full Dolma training dataset, every training checkpoint, training logs, and pretraining/instruction-tuning/RL code, not just final weights among its strengths; NVIDIA Nemotron 3 Ultra does not.
A genuine 32B reasoning ('Think') model that generates explicit chain-of-thought: OLMo 3 32B Think — NVIDIA Nemotron 3 Ultra is comparatively weak here — trails the best Chinese open models on overall intelligence
Fully open under Apache 2.0 - free to self-host: OLMo 3 32B Think — OLMo 3 32B Think lists fully open under Apache 2.0 - free to self-host among its strengths; NVIDIA Nemotron 3 Ultra does not.
Largest single-prompt input: NVIDIA Nemotron 3 Ultra — Its 1M window is about 15× larger than OLMo 3 32B Think's 65K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
Someone analysing very long documents or codebases: NVIDIA Nemotron 3 Ultra — Larger 1M window fits more in one prompt.
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 — It is specifically built for that.
Anyone whose priority is the most fully transparent open release available - ai2 publishes the complete weights, full dolma training dataset, every training checkpoint, training logs, and pretraining/instruction-tuning/rl code, not just final weights: OLMo 3 32B Think — That is its strongest area.
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 are real: 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.
OLMo 3 32B Think: where it fits
Allen Institute for AI's fully-open 32B reasoning model - the rare release that ships the complete training data and process, not just the weights. Released November 20, 2025 by Allen Institute for AI, it is built for the most fully transparent open release available - Ai2 publishes the complete weights, full Dolma training dataset, every training checkpoint, training logs, and pretraining/instruction-tuning/RL code, not just final weights, a genuine 32B reasoning ('Think') model that generates explicit chain-of-thought, fully open under Apache 2.0 - free to self-host, and built specifically to let researchers reproduce and audit exactly how the model was trained.
Its trade-offs: a 65K context window is modest next to million-token frontier models, prioritizes full openness and reproducibility over topping raw capability leaderboards, and 32B scale trails much larger frontier and open MoE models on general benchmarks. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
NVIDIA Nemotron 3 Ultra and OLMo 3 32B Think overlap enough that the right pick depends on your specific job. NVIDIA Nemotron 3 Ultra holds the larger context; and each leads in its own area — NVIDIA Nemotron 3 Ultra for the most capable open-weight model from a us lab (artificial analysis intelligence index of about 48), OLMo 3 32B Think for the most fully transparent open release available - ai2 publishes the complete weights, full dolma training dataset, every training checkpoint, training logs, and pretraining/instruction-tuning/rl code, not just final weights. Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is NVIDIA Nemotron 3 Ultra or OLMo 3 32B Think 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, NVIDIA Nemotron 3 Ultra leans toward the most capable open-weight model from a us lab (artificial analysis intelligence index of about 48) while OLMo 3 32B Think leans toward the most fully transparent open release available - ai2 publishes the complete weights, full dolma training dataset, every training checkpoint, training logs, and pretraining/instruction-tuning/rl code, not just final weights, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, NVIDIA Nemotron 3 Ultra or OLMo 3 32B Think?
They are priced almost identically, so cost will not decide between them.
Which has the bigger context window?
NVIDIA Nemotron 3 Ultra — 1M vs 65K, about 15× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both NVIDIA Nemotron 3 Ultra and OLMo 3 32B Think together?
Yes — a multi-model platform like LumiChats gives you NVIDIA Nemotron 3 Ultra, OLMo 3 32B Think 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, NVIDIA Nemotron 3 Ultra or OLMo 3 32B Think?
NVIDIA Nemotron 3 Ultra — released June 4, 2026, about 7 months after OLMo 3 32B Think.
NVIDIA Nemotron 3 Ultra vs OLMo 3 32B Think
NVIDIA · US | Allen Institute for AI · US · Updated June 2026
Quick verdict
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. Pick OLMo 3 32B Think for the most fully transparent open release available - ai2 publishes the complete weights, full dolma training dataset, every training checkpoint, training logs, and pretraining/instruction-tuning/rl code, not just final weights or a genuine 32b reasoning ('think') model that generates explicit chain-of-thought.
NVIDIA Nemotron 3 Ultra (NVIDIA) and OLMo 3 32B Think (Allen Institute for AI) are two of the models people most often weigh against each other in 2026. 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. OLMo 3 32B Think is allen Institute for AI's fully-open 32B reasoning model - the rare release that ships the complete training data and process, not just the weights. Their biggest split is context window, and the breakdown below shows exactly how that plays out for your workload.
Key differences at a glance
▸Context window: NVIDIA Nemotron 3 Ultra holds 15× more — 1M (~1,500 pages) vs 65K (~98 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 7 months (released June 4, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
NVIDIA Nemotron 3 Ultra
OLMo 3 32B Think
Provider
NVIDIA (US)
Allen Institute for AI (US)
Released
June 4, 2026
November 20, 2025
Context window
1M (~1,500 pages)
65K (~98 pages)
Price (in/out)
Open weight (self-host / free)
Open weight (self-host / free)
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
The most capable open-weight model from a US lab (Artificial Analysis Intelligence Index of about 48)
NVIDIA Nemotron 3 Ultra
OLMo 3 32B Think is comparatively weak here — a 65K context window is modest next to million-token frontier models
Fast, efficient long-horizon agentic reasoning via a hybrid Mamba-Transformer design
NVIDIA Nemotron 3 Ultra
Its 1M window holds about 15× more than OLMo 3 32B Think's 65K 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.
The most fully transparent open release available - Ai2 publishes the complete weights, full Dolma training dataset, every training checkpoint, training logs, and pretraining/instruction-tuning/RL code, not just final weights
OLMo 3 32B Think
OLMo 3 32B Think lists the most fully transparent open release available - Ai2 publishes the complete weights, full Dolma training dataset, every training checkpoint, training logs, and pretraining/instruction-tuning/RL code, not just final weights among its strengths; NVIDIA Nemotron 3 Ultra does not.
A genuine 32B reasoning ('Think') model that generates explicit chain-of-thought
OLMo 3 32B Think
NVIDIA Nemotron 3 Ultra is comparatively weak here — trails the best Chinese open models on overall intelligence
Fully open under Apache 2.0 - free to self-host
OLMo 3 32B Think
OLMo 3 32B Think lists fully open under Apache 2.0 - free to self-host among its strengths; NVIDIA Nemotron 3 Ultra does not.
Largest single-prompt input
NVIDIA Nemotron 3 Ultra
Its 1M window is about 15× larger than OLMo 3 32B Think's 65K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
Someone analysing very long documents or codebases
→ NVIDIA Nemotron 3 Ultra
Larger 1M window fits more in one prompt.
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
It is specifically built for that.
Anyone whose priority is the most fully transparent open release available - ai2 publishes the complete weights, full dolma training dataset, every training checkpoint, training logs, and pretraining/instruction-tuning/rl code, not just final weights
→ OLMo 3 32B Think
That is its strongest area.
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 are real: 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.
OLMo 3 32B Think: where it fits
Allen Institute for AI's fully-open 32B reasoning model - the rare release that ships the complete training data and process, not just the weights. Released November 20, 2025 by Allen Institute for AI, it is built for the most fully transparent open release available - Ai2 publishes the complete weights, full Dolma training dataset, every training checkpoint, training logs, and pretraining/instruction-tuning/RL code, not just final weights, a genuine 32B reasoning ('Think') model that generates explicit chain-of-thought, fully open under Apache 2.0 - free to self-host, and built specifically to let researchers reproduce and audit exactly how the model was trained.
Its trade-offs: a 65K context window is modest next to million-token frontier models, prioritizes full openness and reproducibility over topping raw capability leaderboards, and 32B scale trails much larger frontier and open MoE models on general benchmarks. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
NVIDIA Nemotron 3 Ultra and OLMo 3 32B Think overlap enough that the right pick depends on your specific job. NVIDIA Nemotron 3 Ultra holds the larger context; and each leads in its own area — NVIDIA Nemotron 3 Ultra for the most capable open-weight model from a us lab (artificial analysis intelligence index of about 48), OLMo 3 32B Think for the most fully transparent open release available - ai2 publishes the complete weights, full dolma training dataset, every training checkpoint, training logs, and pretraining/instruction-tuning/rl code, not just final weights. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both NVIDIA Nemotron 3 Ultra and OLMo 3 32B Think 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 NVIDIA Nemotron 3 Ultra or OLMo 3 32B Think 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, NVIDIA Nemotron 3 Ultra leans toward the most capable open-weight model from a us lab (artificial analysis intelligence index of about 48) while OLMo 3 32B Think leans toward the most fully transparent open release available - ai2 publishes the complete weights, full dolma training dataset, every training checkpoint, training logs, and pretraining/instruction-tuning/rl code, not just final weights, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, NVIDIA Nemotron 3 Ultra or OLMo 3 32B Think?
They are priced almost identically, so cost will not decide between them.
Which has the bigger context window?
NVIDIA Nemotron 3 Ultra — 1M vs 65K, about 15× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both NVIDIA Nemotron 3 Ultra and OLMo 3 32B Think together?
Yes — a multi-model platform like LumiChats gives you NVIDIA Nemotron 3 Ultra, OLMo 3 32B Think 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, NVIDIA Nemotron 3 Ultra or OLMo 3 32B Think?
NVIDIA Nemotron 3 Ultra — released June 4, 2026, about 7 months after OLMo 3 32B Think.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.