Pick Gemini 3.1 Flash Lite for ultra-low-latency, high-volume production workloads or most cost-efficient gemini 3 model — half the price of gemini 3 flash ($0.25/$1.50 vs $0.50/$3.00 per 1m tokens). Pick NVIDIA Nemotron 3 Super for high-throughput agentic reasoning (up to 2.2x gpt-oss-120b) or 1m-token context with strong long-context retrieval (91.6% ruler @ 1m). Choose NVIDIA Nemotron 3 Super if you need self-hosting or data privacy; Gemini 3.1 Flash Lite if you want a managed API.
Gemini 3.1 Flash Lite (Google) and NVIDIA Nemotron 3 Super (NVIDIA) are two of the models people most often weigh against each other in 2026. Gemini 3.1 Flash Lite is google's fastest and most cost-efficient Gemini 3 series model, built for ultra-low-latency, high-volume production workloads at half the price of Gemini 3 Flash. NVIDIA Nemotron 3 Super is nVIDIA's open 120B-total/12B-active hybrid Mamba-Transformer MoE built for high-throughput agentic reasoning at 1M-token context. They diverge most on price and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Cost model: NVIDIA Nemotron 3 Super ships open weights you can self-host (hardware cost only, no per-token fee), while Gemini 3.1 Flash Lite is API-metered at $0.25/$1.5 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
Context window: both advertise 1M (~1,500 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
Specifications
Spec
Gemini 3.1 Flash Lite
NVIDIA Nemotron 3 Super
Provider
Google (US)
NVIDIA (US)
Released
March 3, 2026
March 11, 2026
Context window
1M (~1,500 pages)
1M (~1,500 pages)
Price (in/out)
$0.25/$1.5 per 1M tokens
Open weight (self-host / free)
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, audio, video
text, code
SWE-Bench Verified
Not published
60.47%
MRCR v2 @ 1M
12.3%
Not published
Who wins what
Ultra-low-latency, high-volume production workloads: Gemini 3.1 Flash Lite — A core design strength of Gemini 3.1 Flash Lite.
Most cost-efficient Gemini 3 model — half the price of Gemini 3 Flash ($0.25/$1.50 vs $0.50/$3.00 per 1M tokens): Gemini 3.1 Flash Lite — A core design strength of Gemini 3.1 Flash Lite.
High-volume agentic and tool-calling loops where cost per call matters: Gemini 3.1 Flash Lite — A core design strength of Gemini 3.1 Flash Lite.
High-throughput agentic reasoning (up to 2.2x GPT-OSS-120B): NVIDIA Nemotron 3 Super — A core design strength of NVIDIA Nemotron 3 Super.
1M-token context with strong long-context retrieval (91.6% RULER @ 1M): NVIDIA Nemotron 3 Super — A core design strength of NVIDIA Nemotron 3 Super.
Strong math reasoning (90.21% AIME 2025): NVIDIA Nemotron 3 Super — A core design strength of NVIDIA Nemotron 3 Super.
Lowest cost at scale: NVIDIA Nemotron 3 Super — At Open weight (self-host / free), it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Which should you pick?
A cost-sensitive startup shipping high volume: NVIDIA Nemotron 3 Super — At Open weight (self-host / free) it undercuts Gemini 3.1 Flash Lite, and on millions of tokens that margin decides the monthly bill.
A team with data-privacy or self-hosting needs: NVIDIA Nemotron 3 Super — Open weights let you run it on your own hardware; Gemini 3.1 Flash Lite is API-only.
Anyone whose priority is ultra-low-latency, high-volume production workloads: Gemini 3.1 Flash Lite — It is specifically built for that.
Anyone whose priority is high-throughput agentic reasoning (up to 2.2x gpt-oss-120b): NVIDIA Nemotron 3 Super — That is its strongest area.
Gemini 3.1 Flash Lite: where it fits
Google's fastest and most cost-efficient Gemini 3 series model, built for ultra-low-latency, high-volume production workloads at half the price of Gemini 3 Flash. Released March 3, 2026 by Google, it is built for ultra-low-latency, high-volume production workloads, most cost-efficient Gemini 3 model — half the price of Gemini 3 Flash ($0.25/$1.50 vs $0.50/$3.00 per 1M tokens), high-volume agentic and tool-calling loops where cost per call matters, and multimodal input across text, image, video, audio, and PDF.
Its trade-offs are real: lower reasoning and quality ceiling than Gemini 3.1 Pro and the full Gemini 3 Flash tier, sharp long-context degradation — MRCR v2 (8-needle) retrieval falls to ~12% at the full 1M-token window, and closed weights — not downloadable or self-hostable. At $0.25 in / $1.5 out per million tokens, it sits in the budget price band.
NVIDIA Nemotron 3 Super: where it fits
NVIDIA's open 120B-total/12B-active hybrid Mamba-Transformer MoE built for high-throughput agentic reasoning at 1M-token context. Released March 11, 2026 by NVIDIA, it is built for high-throughput agentic reasoning (up to 2.2x GPT-OSS-120B), 1M-token context with strong long-context retrieval (91.6% RULER @ 1M), strong math reasoning (90.21% AIME 2025), and fully open weights, datasets, and recipes for self-hosting.
Its trade-offs: text-only; no image, audio, or video input, and requires roughly 8x H100-80GB GPUs to self-host at BF16. 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 Super gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Gemini 3.1 Flash Lite 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 Flash Lite or NVIDIA Nemotron 3 Super better for coding?
Public SWE-Bench figures are not available for Gemini 3.1 Flash Lite, so the honest test is your own repository — run an identical real bug through both. By design, Gemini 3.1 Flash Lite leans toward ultra-low-latency, high-volume production workloads while NVIDIA Nemotron 3 Super leans toward high-throughput agentic reasoning (up to 2.2x gpt-oss-120b), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Gemini 3.1 Flash Lite or NVIDIA Nemotron 3 Super?
NVIDIA Nemotron 3 Super is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Gemini 3.1 Flash Lite is API-metered at $0.25/$1.5 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?
Both advertise 1M (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Gemini 3.1 Flash Lite and NVIDIA Nemotron 3 Super together?
Yes — a multi-model platform like LumiChats gives you Gemini 3.1 Flash Lite, NVIDIA Nemotron 3 Super 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 Flash Lite or NVIDIA Nemotron 3 Super?
NVIDIA Nemotron 3 Super — released March 11, 2026, about 8 days after Gemini 3.1 Flash Lite.
Gemini 3.1 Flash Lite vs NVIDIA Nemotron 3 Super
Google · US | NVIDIA · US · Updated June 2026
Quick verdict
Pick Gemini 3.1 Flash Lite for ultra-low-latency, high-volume production workloads or most cost-efficient gemini 3 model — half the price of gemini 3 flash ($0.25/$1.50 vs $0.50/$3.00 per 1m tokens). Pick NVIDIA Nemotron 3 Super for high-throughput agentic reasoning (up to 2.2x gpt-oss-120b) or 1m-token context with strong long-context retrieval (91.6% ruler @ 1m). Choose NVIDIA Nemotron 3 Super if you need self-hosting or data privacy; Gemini 3.1 Flash Lite if you want a managed API.
Gemini 3.1 Flash Lite (Google) and NVIDIA Nemotron 3 Super (NVIDIA) are two of the models people most often weigh against each other in 2026. Gemini 3.1 Flash Lite is google's fastest and most cost-efficient Gemini 3 series model, built for ultra-low-latency, high-volume production workloads at half the price of Gemini 3 Flash. NVIDIA Nemotron 3 Super is nVIDIA's open 120B-total/12B-active hybrid Mamba-Transformer MoE built for high-throughput agentic reasoning at 1M-token context. They diverge most on price and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
▸Cost model: NVIDIA Nemotron 3 Super ships open weights you can self-host (hardware cost only, no per-token fee), while Gemini 3.1 Flash Lite is API-metered at $0.25/$1.5 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
▸Context window: both advertise 1M (~1,500 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
Side-by-side specs
Spec
Gemini 3.1 Flash Lite
NVIDIA Nemotron 3 Super
Provider
Google (US)
NVIDIA (US)
Released
March 3, 2026
March 11, 2026
Context window
1M (~1,500 pages)
1M (~1,500 pages)
Price (in/out)
$0.25/$1.5 per 1M tokens
Open weight (self-host / free)
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, audio, video
text, code
SWE-Bench Verified
Not published
60.47%
MRCR v2 @ 1M
12.3%
Not published
Who wins what
Ultra-low-latency, high-volume production workloads
Gemini 3.1 Flash Lite
A core design strength of Gemini 3.1 Flash Lite.
Most cost-efficient Gemini 3 model — half the price of Gemini 3 Flash ($0.25/$1.50 vs $0.50/$3.00 per 1M tokens)
Gemini 3.1 Flash Lite
A core design strength of Gemini 3.1 Flash Lite.
High-volume agentic and tool-calling loops where cost per call matters
Gemini 3.1 Flash Lite
A core design strength of Gemini 3.1 Flash Lite.
High-throughput agentic reasoning (up to 2.2x GPT-OSS-120B)
NVIDIA Nemotron 3 Super
A core design strength of NVIDIA Nemotron 3 Super.
1M-token context with strong long-context retrieval (91.6% RULER @ 1M)
NVIDIA Nemotron 3 Super
A core design strength of NVIDIA Nemotron 3 Super.
Strong math reasoning (90.21% AIME 2025)
NVIDIA Nemotron 3 Super
A core design strength of NVIDIA Nemotron 3 Super.
Lowest cost at scale
NVIDIA Nemotron 3 Super
At Open weight (self-host / free), it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Which should you pick?
A cost-sensitive startup shipping high volume
→ NVIDIA Nemotron 3 Super
At Open weight (self-host / free) it undercuts Gemini 3.1 Flash Lite, and on millions of tokens that margin decides the monthly bill.
A team with data-privacy or self-hosting needs
→ NVIDIA Nemotron 3 Super
Open weights let you run it on your own hardware; Gemini 3.1 Flash Lite is API-only.
Anyone whose priority is ultra-low-latency, high-volume production workloads
→ Gemini 3.1 Flash Lite
It is specifically built for that.
Anyone whose priority is high-throughput agentic reasoning (up to 2.2x gpt-oss-120b)
→ NVIDIA Nemotron 3 Super
That is its strongest area.
Gemini 3.1 Flash Lite: where it fits
Google's fastest and most cost-efficient Gemini 3 series model, built for ultra-low-latency, high-volume production workloads at half the price of Gemini 3 Flash. Released March 3, 2026 by Google, it is built for ultra-low-latency, high-volume production workloads, most cost-efficient Gemini 3 model — half the price of Gemini 3 Flash ($0.25/$1.50 vs $0.50/$3.00 per 1M tokens), high-volume agentic and tool-calling loops where cost per call matters, and multimodal input across text, image, video, audio, and PDF.
Its trade-offs are real: lower reasoning and quality ceiling than Gemini 3.1 Pro and the full Gemini 3 Flash tier, sharp long-context degradation — MRCR v2 (8-needle) retrieval falls to ~12% at the full 1M-token window, and closed weights — not downloadable or self-hostable. At $0.25 in / $1.5 out per million tokens, it sits in the budget price band.
NVIDIA Nemotron 3 Super: where it fits
NVIDIA's open 120B-total/12B-active hybrid Mamba-Transformer MoE built for high-throughput agentic reasoning at 1M-token context. Released March 11, 2026 by NVIDIA, it is built for high-throughput agentic reasoning (up to 2.2x GPT-OSS-120B), 1M-token context with strong long-context retrieval (91.6% RULER @ 1M), strong math reasoning (90.21% AIME 2025), and fully open weights, datasets, and recipes for self-hosting.
Its trade-offs: text-only; no image, audio, or video input, and requires roughly 8x H100-80GB GPUs to self-host at BF16. 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 Super gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Gemini 3.1 Flash Lite 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 Flash Lite and NVIDIA Nemotron 3 Super 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 Flash Lite or NVIDIA Nemotron 3 Super better for coding?
Public SWE-Bench figures are not available for Gemini 3.1 Flash Lite, so the honest test is your own repository — run an identical real bug through both. By design, Gemini 3.1 Flash Lite leans toward ultra-low-latency, high-volume production workloads while NVIDIA Nemotron 3 Super leans toward high-throughput agentic reasoning (up to 2.2x gpt-oss-120b), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Gemini 3.1 Flash Lite or NVIDIA Nemotron 3 Super?
NVIDIA Nemotron 3 Super is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Gemini 3.1 Flash Lite is API-metered at $0.25/$1.5 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?
Both advertise 1M (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Gemini 3.1 Flash Lite and NVIDIA Nemotron 3 Super together?
Yes — a multi-model platform like LumiChats gives you Gemini 3.1 Flash Lite, NVIDIA Nemotron 3 Super 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 Flash Lite or NVIDIA Nemotron 3 Super?
NVIDIA Nemotron 3 Super — released March 11, 2026, about 8 days after Gemini 3.1 Flash Lite.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.