Pick Gemini 3.1 Pro for full multimodal input — text, image, audio and video in one 1m-token window or long video and document analysis. 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. Choose NVIDIA Nemotron 3 Ultra if you need self-hosting or data privacy; Gemini 3.1 Pro if you want a managed API.
Gemini 3.1 Pro (Google) and NVIDIA Nemotron 3 Ultra (NVIDIA) are two of the models people most often weigh against each other in 2026. Gemini 3.1 Pro is a 1M-token multimodal workhorse — huge breadth across text, image, audio and video, but recall fades deep in the window. 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, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Cost model: NVIDIA Nemotron 3 Ultra ships open weights you can self-host (hardware cost only, no per-token fee), while Gemini 3.1 Pro is API-metered at $2/$12 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
Context window: 1M vs 1M — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
Recency: NVIDIA Nemotron 3 Ultra is the newer model by about 4 months (released June 4, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Gemini 3.1 Pro
NVIDIA Nemotron 3 Ultra
Provider
Google (US)
NVIDIA (US)
Released
February 19, 2026
June 4, 2026
Context window
1M (~1,573 pages)
1M (~1,500 pages)
Price (in/out)
$2/$12 per 1M tokens
Open weight (self-host / free)
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, audio, video, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
26.3%
Not published
Who wins what
Full multimodal input — text, image, audio and video in one 1M-token window: Gemini 3.1 Pro — Gemini 3.1 Pro lists full multimodal input — text, image, audio and video in one 1M-token window among its strengths; NVIDIA Nemotron 3 Ultra does not.
Long video and document analysis: Gemini 3.1 Pro — Gemini 3.1 Pro lists long video and document analysis among its strengths; NVIDIA Nemotron 3 Ultra does not.
Agentic reasoning (high ARC-AGI-2): Gemini 3.1 Pro — Gemini 3.1 Pro lists agentic reasoning (high ARC-AGI-2) 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 — Open weights make this possible at all — Gemini 3.1 Pro is API-only, so it cannot leave the vendor's servers.
Fast, efficient long-horizon agentic reasoning via a hybrid Mamba-Transformer design: 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 its weights are open while Gemini 3.1 Pro is API-only.
A fully open release — weights, training data, and recipes under a permissive license: NVIDIA Nemotron 3 Ultra — Gemini 3.1 Pro is comparatively weak here — superseded within Google's own line by the newer 3.5/3.6 Flash releases for cost-sensitive work
Lowest cost at scale: NVIDIA Nemotron 3 Ultra — Its weights are open, so at volume you pay for your own hardware instead of Gemini 3.1 Pro's $2/$12 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume: NVIDIA Nemotron 3 Ultra — At Open weight (self-host / free) it undercuts Gemini 3.1 Pro, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Gemini 3.1 Pro — Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs: NVIDIA Nemotron 3 Ultra — Open weights let you run it on your own hardware; Gemini 3.1 Pro is API-only.
Anyone whose priority is full multimodal input — text, image, audio and video in one 1m-token window: Gemini 3.1 Pro — 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.
Gemini 3.1 Pro: where it fits
A 1M-token multimodal workhorse — huge breadth across text, image, audio and video, but recall fades deep in the window. Released February 19, 2026 by Google, it is built for full multimodal input — text, image, audio and video in one 1M-token window, long video and document analysis, agentic reasoning (high ARC-AGI-2), and broad multimodal understanding across formats.
Its trade-offs are real: long-context recall drops sharply past 256K (26.3% on MRCR v2 at 1M), premium price per token at $2/$12, and superseded within Google's own line by the newer 3.5/3.6 Flash releases for cost-sensitive work. At $2 in / $12 out per million tokens, it sits in the mid 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
The defining split here is open vs. closed. NVIDIA Nemotron 3 Ultra gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Gemini 3.1 Pro gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.
Frequently asked questions
Is Gemini 3.1 Pro 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, Gemini 3.1 Pro leans toward full multimodal input — text, image, audio and video in one 1m-token window 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, Gemini 3.1 Pro or NVIDIA Nemotron 3 Ultra?
NVIDIA Nemotron 3 Ultra is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Gemini 3.1 Pro is API-metered at $2/$12 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?
Effectively neither — 1M vs 1M is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Gemini 3.1 Pro and NVIDIA Nemotron 3 Ultra together?
Yes — a multi-model platform like LumiChats gives you Gemini 3.1 Pro, 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, Gemini 3.1 Pro or NVIDIA Nemotron 3 Ultra?
NVIDIA Nemotron 3 Ultra — released June 4, 2026, about 4 months after Gemini 3.1 Pro.
Gemini 3.1 Pro vs NVIDIA Nemotron 3 Ultra
Google · US | NVIDIA · US · Updated June 2026
Quick verdict
Pick Gemini 3.1 Pro for full multimodal input — text, image, audio and video in one 1m-token window or long video and document analysis. 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. Choose NVIDIA Nemotron 3 Ultra if you need self-hosting or data privacy; Gemini 3.1 Pro if you want a managed API.
Gemini 3.1 Pro (Google) and NVIDIA Nemotron 3 Ultra (NVIDIA) are two of the models people most often weigh against each other in 2026. Gemini 3.1 Pro is a 1M-token multimodal workhorse — huge breadth across text, image, audio and video, but recall fades deep in the window. 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, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
▸Cost model: NVIDIA Nemotron 3 Ultra ships open weights you can self-host (hardware cost only, no per-token fee), while Gemini 3.1 Pro is API-metered at $2/$12 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
▸Context window: 1M vs 1M — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
▸Recency: NVIDIA Nemotron 3 Ultra is the newer model by about 4 months (released June 4, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Gemini 3.1 Pro
NVIDIA Nemotron 3 Ultra
Provider
Google (US)
NVIDIA (US)
Released
February 19, 2026
June 4, 2026
Context window
1M (~1,573 pages)
1M (~1,500 pages)
Price (in/out)
$2/$12 per 1M tokens
Open weight (self-host / free)
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, audio, video, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
26.3%
Not published
Who wins what
Full multimodal input — text, image, audio and video in one 1M-token window
Gemini 3.1 Pro
Gemini 3.1 Pro lists full multimodal input — text, image, audio and video in one 1M-token window among its strengths; NVIDIA Nemotron 3 Ultra does not.
Long video and document analysis
Gemini 3.1 Pro
Gemini 3.1 Pro lists long video and document analysis among its strengths; NVIDIA Nemotron 3 Ultra does not.
Agentic reasoning (high ARC-AGI-2)
Gemini 3.1 Pro
Gemini 3.1 Pro lists agentic reasoning (high ARC-AGI-2) 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
Open weights make this possible at all — Gemini 3.1 Pro is API-only, so it cannot leave the vendor's servers.
Fast, efficient long-horizon agentic reasoning via a hybrid Mamba-Transformer design
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 its weights are open while Gemini 3.1 Pro is API-only.
A fully open release — weights, training data, and recipes under a permissive license
NVIDIA Nemotron 3 Ultra
Gemini 3.1 Pro is comparatively weak here — superseded within Google's own line by the newer 3.5/3.6 Flash releases for cost-sensitive work
Lowest cost at scale
NVIDIA Nemotron 3 Ultra
Its weights are open, so at volume you pay for your own hardware instead of Gemini 3.1 Pro's $2/$12 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume
→ NVIDIA Nemotron 3 Ultra
At Open weight (self-host / free) it undercuts Gemini 3.1 Pro, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Gemini 3.1 Pro
Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ NVIDIA Nemotron 3 Ultra
Open weights let you run it on your own hardware; Gemini 3.1 Pro is API-only.
Anyone whose priority is full multimodal input — text, image, audio and video in one 1m-token window
→ Gemini 3.1 Pro
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.
Gemini 3.1 Pro: where it fits
A 1M-token multimodal workhorse — huge breadth across text, image, audio and video, but recall fades deep in the window. Released February 19, 2026 by Google, it is built for full multimodal input — text, image, audio and video in one 1M-token window, long video and document analysis, agentic reasoning (high ARC-AGI-2), and broad multimodal understanding across formats.
Its trade-offs are real: long-context recall drops sharply past 256K (26.3% on MRCR v2 at 1M), premium price per token at $2/$12, and superseded within Google's own line by the newer 3.5/3.6 Flash releases for cost-sensitive work. At $2 in / $12 out per million tokens, it sits in the mid 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
The defining split here is open vs. closed. NVIDIA Nemotron 3 Ultra gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Gemini 3.1 Pro gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.
Want both Gemini 3.1 Pro 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 Gemini 3.1 Pro 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, Gemini 3.1 Pro leans toward full multimodal input — text, image, audio and video in one 1m-token window 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, Gemini 3.1 Pro or NVIDIA Nemotron 3 Ultra?
NVIDIA Nemotron 3 Ultra is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Gemini 3.1 Pro is API-metered at $2/$12 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?
Effectively neither — 1M vs 1M is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Gemini 3.1 Pro and NVIDIA Nemotron 3 Ultra together?
Yes — a multi-model platform like LumiChats gives you Gemini 3.1 Pro, 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, Gemini 3.1 Pro or NVIDIA Nemotron 3 Ultra?
NVIDIA Nemotron 3 Ultra — released June 4, 2026, about 4 months after Gemini 3.1 Pro.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.