Pick Amazon Nova Premier for 1m-token context with deep aws bedrock integration or amazon's most capable nova model, positioned as a 'teacher' for distilling smaller models. 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 Premier if you want a managed API.
Amazon Nova Premier (Amazon) and NVIDIA Nemotron 3 Super (NVIDIA) are two of the models people most often weigh against each other in 2026. Amazon Nova Premier is amazon's flagship 1M-context Nova model on AWS Bedrock - a useful ecosystem anchor and distillation teacher, but weak and pricey on independent intelligence. 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 Amazon Nova Premier is API-metered at $2.5/$12.5 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.
Recency: NVIDIA Nemotron 3 Super is the newer model by about 11 months (released March 11, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Amazon Nova Premier
NVIDIA Nemotron 3 Super
Provider
Amazon (US)
NVIDIA (US)
Released
April 30, 2025
March 11, 2026
Context window
1M (~1,500 pages)
1M (~1,500 pages)
Price (in/out)
$2.5/$12.5 per 1M tokens
Open weight (self-host / free)
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image
text, code
SWE-Bench Verified
Not published
60.47%
MRCR v2 @ 1M
Not published
Not published
Who wins what
1M-token context with deep AWS Bedrock integration: Amazon Nova Premier — Amazon Nova Premier lists 1M-token context with deep AWS Bedrock integration among its strengths; NVIDIA Nemotron 3 Super does not.
Amazon's most capable Nova model, positioned as a 'teacher' for distilling smaller models: Amazon Nova Premier — Amazon Nova Premier lists amazon's most capable Nova model, positioned as a 'teacher' for distilling smaller models among its strengths; NVIDIA Nemotron 3 Super does not.
A natural fit for teams already building on AWS: Amazon Nova Premier — Amazon Nova Premier lists a natural fit for teams already building on AWS among its strengths; NVIDIA Nemotron 3 Super does not.
High-throughput agentic reasoning (up to 2.2x GPT-OSS-120B): 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 its weights are open while Amazon Nova Premier is API-only.
1M-token context with strong long-context retrieval (91.6% RULER @ 1M): NVIDIA Nemotron 3 Super — Amazon Nova Premier is comparatively weak here — expensive for its score at $2.50/$12.50 per million tokens
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 is the newer of the two.
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 Premier's $2.5/$12.5 per 1M tokens.
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 Premier, 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; Amazon Nova Premier is API-only.
Anyone whose priority is 1m-token context with deep aws bedrock integration: Amazon Nova Premier — 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 Premier: where it fits
Amazon's flagship 1M-context Nova model on AWS Bedrock - a useful ecosystem anchor and distillation teacher, but weak and pricey on independent intelligence. Released April 30, 2025 by Amazon, it is built for 1M-token context with deep AWS Bedrock integration, amazon's most capable Nova model, positioned as a 'teacher' for distilling smaller models, a natural fit for teams already building on AWS, and multimodal input for complex reasoning across text and images.
Its trade-offs are real: weak on independent intelligence - Artificial Analysis Intelligence Index of 13, below average for its tier, expensive for its score at $2.50/$12.50 per million tokens, a 2025 model - older than the 2026 frontier it competes against, and sources disagree on modalities (Amazon cites image input; some evaluations list text-only). At $2.5 in / $12.5 out per million tokens, it sits in the mid 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 Premier 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 Premier or NVIDIA Nemotron 3 Super better for coding?
Public SWE-Bench figures are not available for Amazon Nova Premier, so the honest test is your own repository — run an identical real bug through both. By design, Amazon Nova Premier leans toward 1m-token context with deep aws bedrock integration 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 Premier 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 Premier is API-metered at $2.5/$12.5 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 Amazon Nova Premier and NVIDIA Nemotron 3 Super together?
Yes — a multi-model platform like LumiChats gives you Amazon Nova Premier, 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 Premier or NVIDIA Nemotron 3 Super?
NVIDIA Nemotron 3 Super — released March 11, 2026, about 11 months after Amazon Nova Premier.
Amazon Nova Premier vs NVIDIA Nemotron 3 Super
Amazon · US | NVIDIA · US · Updated June 2026
Quick verdict
Pick Amazon Nova Premier for 1m-token context with deep aws bedrock integration or amazon's most capable nova model, positioned as a 'teacher' for distilling smaller models. 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 Premier if you want a managed API.
Amazon Nova Premier (Amazon) and NVIDIA Nemotron 3 Super (NVIDIA) are two of the models people most often weigh against each other in 2026. Amazon Nova Premier is amazon's flagship 1M-context Nova model on AWS Bedrock - a useful ecosystem anchor and distillation teacher, but weak and pricey on independent intelligence. 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 Amazon Nova Premier is API-metered at $2.5/$12.5 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.
▸Recency: NVIDIA Nemotron 3 Super is the newer model by about 11 months (released March 11, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Amazon Nova Premier
NVIDIA Nemotron 3 Super
Provider
Amazon (US)
NVIDIA (US)
Released
April 30, 2025
March 11, 2026
Context window
1M (~1,500 pages)
1M (~1,500 pages)
Price (in/out)
$2.5/$12.5 per 1M tokens
Open weight (self-host / free)
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image
text, code
SWE-Bench Verified
Not published
60.47%
MRCR v2 @ 1M
Not published
Not published
Who wins what
1M-token context with deep AWS Bedrock integration
Amazon Nova Premier
Amazon Nova Premier lists 1M-token context with deep AWS Bedrock integration among its strengths; NVIDIA Nemotron 3 Super does not.
Amazon's most capable Nova model, positioned as a 'teacher' for distilling smaller models
Amazon Nova Premier
Amazon Nova Premier lists amazon's most capable Nova model, positioned as a 'teacher' for distilling smaller models among its strengths; NVIDIA Nemotron 3 Super does not.
A natural fit for teams already building on AWS
Amazon Nova Premier
Amazon Nova Premier lists a natural fit for teams already building on AWS among its strengths; NVIDIA Nemotron 3 Super does not.
High-throughput agentic reasoning (up to 2.2x GPT-OSS-120B)
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 its weights are open while Amazon Nova Premier is API-only.
1M-token context with strong long-context retrieval (91.6% RULER @ 1M)
NVIDIA Nemotron 3 Super
Amazon Nova Premier is comparatively weak here — expensive for its score at $2.50/$12.50 per million tokens
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 is the newer of the two.
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 Premier's $2.5/$12.5 per 1M tokens.
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 Premier, 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; Amazon Nova Premier is API-only.
Anyone whose priority is 1m-token context with deep aws bedrock integration
→ Amazon Nova Premier
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 Premier: where it fits
Amazon's flagship 1M-context Nova model on AWS Bedrock - a useful ecosystem anchor and distillation teacher, but weak and pricey on independent intelligence. Released April 30, 2025 by Amazon, it is built for 1M-token context with deep AWS Bedrock integration, amazon's most capable Nova model, positioned as a 'teacher' for distilling smaller models, a natural fit for teams already building on AWS, and multimodal input for complex reasoning across text and images.
Its trade-offs are real: weak on independent intelligence - Artificial Analysis Intelligence Index of 13, below average for its tier, expensive for its score at $2.50/$12.50 per million tokens, a 2025 model - older than the 2026 frontier it competes against, and sources disagree on modalities (Amazon cites image input; some evaluations list text-only). At $2.5 in / $12.5 out per million tokens, it sits in the mid 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 Premier 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 Premier 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 Premier or NVIDIA Nemotron 3 Super better for coding?
Public SWE-Bench figures are not available for Amazon Nova Premier, so the honest test is your own repository — run an identical real bug through both. By design, Amazon Nova Premier leans toward 1m-token context with deep aws bedrock integration 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 Premier 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 Premier is API-metered at $2.5/$12.5 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 Amazon Nova Premier and NVIDIA Nemotron 3 Super together?
Yes — a multi-model platform like LumiChats gives you Amazon Nova Premier, 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 Premier or NVIDIA Nemotron 3 Super?
NVIDIA Nemotron 3 Super — released March 11, 2026, about 11 months after Amazon Nova Premier.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.