Pick Amazon Nova Pro for multimodal input across text, image and video at $0.80/$3.20 or deep aws and bedrock integration for enterprise pipelines. 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; Amazon Nova Pro if you want a managed API.
Amazon Nova Pro (Amazon) and NVIDIA Nemotron 3 Super (NVIDIA) are two of the models people most often weigh against each other in 2026. Amazon Nova Pro is amazon's multimodal Bedrock model at $0.80/$3.20 with a 300K window — an enterprise-integrated generalist, not a frontier model. 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, context window 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 Amazon Nova Pro is API-metered at $0.8/$3.2 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
Context window: NVIDIA Nemotron 3 Super holds 3.3× more — 1M (~1,500 pages) vs 300K (~450 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 Super is the newer model by about 15 months (released March 11, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Amazon Nova Pro
NVIDIA Nemotron 3 Super
Provider
Amazon (US)
NVIDIA (US)
Released
December 5, 2024
March 11, 2026
Context window
300K (~450 pages)
1M (~1,500 pages)
Price (in/out)
$0.8/$3.2 per 1M tokens
Open weight (self-host / free)
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, video, code
text, code
SWE-Bench Verified
Not published
60.47%
MRCR v2 @ 1M
Not published
Not published
Who wins what
Multimodal input across text, image and video at $0.80/$3.20: Amazon Nova Pro — NVIDIA Nemotron 3 Super is comparatively weak here — text-only; no image, audio, or video input
Deep AWS and Bedrock integration for enterprise pipelines: Amazon Nova Pro — Amazon Nova Pro lists deep AWS and Bedrock integration for enterprise pipelines among its strengths; NVIDIA Nemotron 3 Super does not.
Balanced cost-to-capability for general business tasks: Amazon Nova Pro — Amazon Nova Pro lists balanced cost-to-capability for general business tasks among its strengths; NVIDIA Nemotron 3 Super does not.
High-throughput agentic reasoning (up to 2.2x GPT-OSS-120B): NVIDIA Nemotron 3 Super — Amazon Nova Pro is comparatively weak here — not a frontier reasoning or coding model against 2026 flagships
1M-token context with strong long-context retrieval (91.6% RULER @ 1M): NVIDIA Nemotron 3 Super — Its 1M window holds about 3.3× more than Amazon Nova Pro's 300K in a single prompt.
Strong math reasoning (90.21% AIME 2025): NVIDIA Nemotron 3 Super — NVIDIA's open 120B-total/12B-active hybrid Mamba-Transformer MoE built for high-throughput agentic reasoning at 1M-token context — and it carries the larger 1M context.
Lowest cost at scale: NVIDIA Nemotron 3 Super — Its weights are open, so at volume you pay for your own hardware instead of Amazon Nova Pro's $0.8/$3.2 per 1M tokens.
Largest single-prompt input: NVIDIA Nemotron 3 Super — Its 1M window is about 3.3× larger than Amazon Nova Pro's 300K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: NVIDIA Nemotron 3 Super — At Open weight (self-host / free) it undercuts Amazon Nova Pro, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: NVIDIA Nemotron 3 Super — Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs: NVIDIA Nemotron 3 Super — Open weights let you run it on your own hardware; Amazon Nova Pro is API-only.
Anyone whose priority is multimodal input across text, image and video at $0.80/$3.20: Amazon Nova Pro — 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.
Amazon Nova Pro: where it fits
Amazon's multimodal Bedrock model at $0.80/$3.20 with a 300K window — an enterprise-integrated generalist, not a frontier model. Released December 5, 2024 by Amazon, it is built for multimodal input across text, image and video at $0.80/$3.20, deep AWS and Bedrock integration for enterprise pipelines, balanced cost-to-capability for general business tasks, and a 300K context for long documents and mixed media.
Its trade-offs are real: not a frontier reasoning or coding model against 2026 flagships, no published SWE-Bench Verified score, best value is realised inside the AWS ecosystem, and late-2024 model — older than most of the field here. At $0.8 in / $3.2 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. Amazon Nova 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 Amazon Nova Pro or NVIDIA Nemotron 3 Super better for coding?
Public SWE-Bench figures are not available for Amazon Nova Pro, so the honest test is your own repository — run an identical real bug through both. By design, Amazon Nova Pro leans toward multimodal input across text, image and video at $0.80/$3.20 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, Amazon Nova Pro 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 Amazon Nova Pro is API-metered at $0.8/$3.2 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?
NVIDIA Nemotron 3 Super — 1M vs 300K, about 3.3× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Amazon Nova Pro and NVIDIA Nemotron 3 Super together?
Yes — a multi-model platform like LumiChats gives you Amazon Nova Pro, 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, Amazon Nova Pro or NVIDIA Nemotron 3 Super?
NVIDIA Nemotron 3 Super — released March 11, 2026, about 15 months after Amazon Nova Pro.
Amazon Nova Pro vs NVIDIA Nemotron 3 Super
Amazon · US | NVIDIA · US · Updated June 2026
Quick verdict
Pick Amazon Nova Pro for multimodal input across text, image and video at $0.80/$3.20 or deep aws and bedrock integration for enterprise pipelines. 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; Amazon Nova Pro if you want a managed API.
Amazon Nova Pro (Amazon) and NVIDIA Nemotron 3 Super (NVIDIA) are two of the models people most often weigh against each other in 2026. Amazon Nova Pro is amazon's multimodal Bedrock model at $0.80/$3.20 with a 300K window — an enterprise-integrated generalist, not a frontier model. 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, 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 Super ships open weights you can self-host (hardware cost only, no per-token fee), while Amazon Nova Pro is API-metered at $0.8/$3.2 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
▸Context window: NVIDIA Nemotron 3 Super holds 3.3× more — 1M (~1,500 pages) vs 300K (~450 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 Super is the newer model by about 15 months (released March 11, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Amazon Nova Pro
NVIDIA Nemotron 3 Super
Provider
Amazon (US)
NVIDIA (US)
Released
December 5, 2024
March 11, 2026
Context window
300K (~450 pages)
1M (~1,500 pages)
Price (in/out)
$0.8/$3.2 per 1M tokens
Open weight (self-host / free)
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, video, code
text, code
SWE-Bench Verified
Not published
60.47%
MRCR v2 @ 1M
Not published
Not published
Who wins what
Multimodal input across text, image and video at $0.80/$3.20
Amazon Nova Pro
NVIDIA Nemotron 3 Super is comparatively weak here — text-only; no image, audio, or video input
Deep AWS and Bedrock integration for enterprise pipelines
Amazon Nova Pro
Amazon Nova Pro lists deep AWS and Bedrock integration for enterprise pipelines among its strengths; NVIDIA Nemotron 3 Super does not.
Balanced cost-to-capability for general business tasks
Amazon Nova Pro
Amazon Nova Pro lists balanced cost-to-capability for general business tasks among its strengths; NVIDIA Nemotron 3 Super does not.
High-throughput agentic reasoning (up to 2.2x GPT-OSS-120B)
NVIDIA Nemotron 3 Super
Amazon Nova Pro is comparatively weak here — not a frontier reasoning or coding model against 2026 flagships
1M-token context with strong long-context retrieval (91.6% RULER @ 1M)
NVIDIA Nemotron 3 Super
Its 1M window holds about 3.3× more than Amazon Nova Pro's 300K in a single prompt.
Strong math reasoning (90.21% AIME 2025)
NVIDIA Nemotron 3 Super
NVIDIA's open 120B-total/12B-active hybrid Mamba-Transformer MoE built for high-throughput agentic reasoning at 1M-token context — and it carries the larger 1M context.
Lowest cost at scale
NVIDIA Nemotron 3 Super
Its weights are open, so at volume you pay for your own hardware instead of Amazon Nova Pro's $0.8/$3.2 per 1M tokens.
Largest single-prompt input
NVIDIA Nemotron 3 Super
Its 1M window is about 3.3× larger than Amazon Nova Pro's 300K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ NVIDIA Nemotron 3 Super
At Open weight (self-host / free) it undercuts Amazon Nova Pro, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ NVIDIA Nemotron 3 Super
Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ NVIDIA Nemotron 3 Super
Open weights let you run it on your own hardware; Amazon Nova Pro is API-only.
Anyone whose priority is multimodal input across text, image and video at $0.80/$3.20
→ Amazon Nova Pro
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.
Amazon Nova Pro: where it fits
Amazon's multimodal Bedrock model at $0.80/$3.20 with a 300K window — an enterprise-integrated generalist, not a frontier model. Released December 5, 2024 by Amazon, it is built for multimodal input across text, image and video at $0.80/$3.20, deep AWS and Bedrock integration for enterprise pipelines, balanced cost-to-capability for general business tasks, and a 300K context for long documents and mixed media.
Its trade-offs are real: not a frontier reasoning or coding model against 2026 flagships, no published SWE-Bench Verified score, best value is realised inside the AWS ecosystem, and late-2024 model — older than most of the field here. At $0.8 in / $3.2 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. Amazon Nova 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 Amazon Nova Pro 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 Amazon Nova Pro or NVIDIA Nemotron 3 Super better for coding?
Public SWE-Bench figures are not available for Amazon Nova Pro, so the honest test is your own repository — run an identical real bug through both. By design, Amazon Nova Pro leans toward multimodal input across text, image and video at $0.80/$3.20 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, Amazon Nova Pro 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 Amazon Nova Pro is API-metered at $0.8/$3.2 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?
NVIDIA Nemotron 3 Super — 1M vs 300K, about 3.3× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Amazon Nova Pro and NVIDIA Nemotron 3 Super together?
Yes — a multi-model platform like LumiChats gives you Amazon Nova Pro, 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, Amazon Nova Pro or NVIDIA Nemotron 3 Super?
NVIDIA Nemotron 3 Super — released March 11, 2026, about 15 months after Amazon Nova 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.