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 DeepSeek V4-Pro for open-weight 1.6t moe (~49b active) — deepseek's largest, self-hostable or 1m-token context with up to 384k output tokens. Choose DeepSeek V4-Pro if you need self-hosting or data privacy; Amazon Nova Premier if you want a managed API.
Amazon Nova Premier (Amazon, US) and DeepSeek V4-Pro (DeepSeek, China) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. 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. DeepSeek V4-Pro is deepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices. They diverge most on price and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Price: DeepSeek V4-Pro is about 5.7× cheaper on input ($0.435/$0.87 per 1M tokens vs $2.5/$12.5 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
Context window: both advertise 1M (~1,500 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
Recency: DeepSeek V4-Pro is the newer model by about 12 months (released April 24, 2026), usually meaning fresher training data and capabilities.
Ecosystem: this is a US-vs-China matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Specifications
Spec
Amazon Nova Premier
DeepSeek V4-Pro
Provider
Amazon (US)
DeepSeek (China)
Released
April 30, 2025
April 24, 2026
Context window
1M (~1,500 pages)
1M (~1,500 pages)
Price (in/out)
$2.5/$12.5 per 1M tokens
$0.435/$0.87 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image
text, code
SWE-Bench Verified
Not published
Not published
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; DeepSeek V4-Pro 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; DeepSeek V4-Pro does not.
A natural fit for teams already building on AWS: Amazon Nova Premier — DeepSeek V4-Pro is comparatively weak here — overlaps DeepSeek V4 and V3.2 already in this comparison
Open-weight 1.6T MoE (~49B active) — DeepSeek's largest, self-hostable: DeepSeek V4-Pro — Open weights make this possible at all — Amazon Nova Premier is API-only, so it cannot leave the vendor's servers.
1M-token context with up to 384K output tokens: DeepSeek V4-Pro — Amazon Nova Premier is comparatively weak here — expensive for its score at $2.50/$12.50 per million tokens
Permanent low pricing at $0.435/$0.87 per million, set May 2026: DeepSeek V4-Pro — DeepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices — and it runs cheaper at $0.435/$0.87 per 1M tokens.
Lowest cost at scale: DeepSeek V4-Pro — At $0.435/$0.87 per 1M tokens, 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: DeepSeek V4-Pro — At $0.435/$0.87 per 1M tokens 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: DeepSeek V4-Pro — 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 open-weight 1.6t moe (~49b active) — deepseek's largest, self-hostable: DeepSeek V4-Pro — That is its strongest area.
An enterprise with regional data-residency rules: Amazon Nova Premier or DeepSeek V4-Pro — Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
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.
DeepSeek V4-Pro: where it fits
DeepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices. Released April 24, 2026 by DeepSeek, it is built for open-weight 1.6T MoE (~49B active) — DeepSeek's largest, self-hostable, 1M-token context with up to 384K output tokens, permanent low pricing at $0.435/$0.87 per million, set May 2026, and sources place it near the top of open-weight coding, around 80 on SWE-Bench Verified.
Its trade-offs: independent SWE-Bench Verified placement is inconsistent across sources, pro and Pro-Max variants are quoted with different scores, text and code only — no image, audio or video, and overlaps DeepSeek V4 and V3.2 already in this comparison. At $0.435 in / $0.87 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
The defining split here is open vs. closed. DeepSeek V4-Pro 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 DeepSeek V4-Pro 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, Amazon Nova Premier leans toward 1m-token context with deep aws bedrock integration while DeepSeek V4-Pro leans toward open-weight 1.6t moe (~49b active) — deepseek's largest, self-hostable, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Amazon Nova Premier or DeepSeek V4-Pro?
DeepSeek V4-Pro 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 DeepSeek V4-Pro together?
Yes — a multi-model platform like LumiChats gives you Amazon Nova Premier, DeepSeek V4-Pro 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 DeepSeek V4-Pro?
DeepSeek V4-Pro — released April 24, 2026, about 12 months after Amazon Nova Premier.
Amazon Nova Premier vs DeepSeek V4-Pro
Amazon · US | DeepSeek · China · 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 DeepSeek V4-Pro for open-weight 1.6t moe (~49b active) — deepseek's largest, self-hostable or 1m-token context with up to 384k output tokens. Choose DeepSeek V4-Pro if you need self-hosting or data privacy; Amazon Nova Premier if you want a managed API.
Amazon Nova Premier (Amazon, US) and DeepSeek V4-Pro (DeepSeek, China) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. 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. DeepSeek V4-Pro is deepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices. They diverge most on price and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
▸Price: DeepSeek V4-Pro is about 5.7× cheaper on input ($0.435/$0.87 per 1M tokens vs $2.5/$12.5 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
▸Context window: both advertise 1M (~1,500 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
▸Recency: DeepSeek V4-Pro is the newer model by about 12 months (released April 24, 2026), usually meaning fresher training data and capabilities.
▸Ecosystem: this is a US-vs-China matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
Spec
Amazon Nova Premier
DeepSeek V4-Pro
Provider
Amazon (US)
DeepSeek (China)
Released
April 30, 2025
April 24, 2026
Context window
1M (~1,500 pages)
1M (~1,500 pages)
Price (in/out)
$2.5/$12.5 per 1M tokens
$0.435/$0.87 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image
text, code
SWE-Bench Verified
Not published
Not published
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; DeepSeek V4-Pro 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; DeepSeek V4-Pro does not.
A natural fit for teams already building on AWS
Amazon Nova Premier
DeepSeek V4-Pro is comparatively weak here — overlaps DeepSeek V4 and V3.2 already in this comparison
Open weights make this possible at all — Amazon Nova Premier is API-only, so it cannot leave the vendor's servers.
1M-token context with up to 384K output tokens
DeepSeek V4-Pro
Amazon Nova Premier is comparatively weak here — expensive for its score at $2.50/$12.50 per million tokens
Permanent low pricing at $0.435/$0.87 per million, set May 2026
DeepSeek V4-Pro
DeepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices — and it runs cheaper at $0.435/$0.87 per 1M tokens.
Lowest cost at scale
DeepSeek V4-Pro
At $0.435/$0.87 per 1M tokens, 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
→ DeepSeek V4-Pro
At $0.435/$0.87 per 1M tokens 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
→ DeepSeek V4-Pro
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
Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
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.
DeepSeek V4-Pro: where it fits
DeepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices. Released April 24, 2026 by DeepSeek, it is built for open-weight 1.6T MoE (~49B active) — DeepSeek's largest, self-hostable, 1M-token context with up to 384K output tokens, permanent low pricing at $0.435/$0.87 per million, set May 2026, and sources place it near the top of open-weight coding, around 80 on SWE-Bench Verified.
Its trade-offs: independent SWE-Bench Verified placement is inconsistent across sources, pro and Pro-Max variants are quoted with different scores, text and code only — no image, audio or video, and overlaps DeepSeek V4 and V3.2 already in this comparison. At $0.435 in / $0.87 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
The defining split here is open vs. closed. DeepSeek V4-Pro 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 DeepSeek V4-Pro 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 DeepSeek V4-Pro 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, Amazon Nova Premier leans toward 1m-token context with deep aws bedrock integration while DeepSeek V4-Pro leans toward open-weight 1.6t moe (~49b active) — deepseek's largest, self-hostable, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Amazon Nova Premier or DeepSeek V4-Pro?
DeepSeek V4-Pro 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 DeepSeek V4-Pro together?
Yes — a multi-model platform like LumiChats gives you Amazon Nova Premier, DeepSeek V4-Pro 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 DeepSeek V4-Pro?
DeepSeek V4-Pro — released April 24, 2026, about 12 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.