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 DeepSeek V4 for near-frontier coding at ~1/12 the cost or open mit-licensed weights you can self-host. Choose DeepSeek V4 if you need self-hosting or data privacy; Amazon Nova Pro if you want a managed API.
Amazon Nova Pro (Amazon, US) and DeepSeek V4 (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 Pro is amazon's multimodal Bedrock model at $0.80/$3.20 with a 300K window — an enterprise-integrated generalist, not a frontier model. DeepSeek V4 is china's open-weight price earthquake — near-frontier capability at roughly a twelfth of GPT-5.5's cost. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Price: DeepSeek V4 is about 1.8× cheaper on input ($0.435/$0.87 per 1M tokens vs $0.8/$3.2 per 1M tokens) — modest, but it adds up at steady volume.
Context window: DeepSeek V4 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: DeepSeek V4 is the newer model by about 17 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 Pro
DeepSeek V4
Provider
Amazon (US)
DeepSeek (China)
Released
December 5, 2024
April 24, 2026
Context window
300K (~450 pages)
1M (~1,500 pages)
Price (in/out)
$0.8/$3.2 per 1M tokens
$0.435/$0.87 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, video, code
text, code
SWE-Bench Verified
Not published
80.6%
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 — DeepSeek V4 is comparatively weak here — text/code focused, less multimodal
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; DeepSeek V4 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; DeepSeek V4 does not.
Near-frontier coding at ~1/12 the cost: DeepSeek V4 — At $0.435/$0.87 per 1M tokens it undercuts Amazon Nova Pro ($0.8/$3.2 per 1M tokens), and that gap compounds at volume.
Open MIT-licensed weights you can self-host: DeepSeek V4 — Open weights make this possible at all — Amazon Nova Pro is API-only, so it cannot leave the vendor's servers.
No long-context surcharge: DeepSeek V4 — Its 1M window holds about 3.3× more than Amazon Nova Pro's 300K in a single prompt.
Lowest cost at scale: DeepSeek V4 — At $0.435/$0.87 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: DeepSeek V4 — 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: DeepSeek V4 — At $0.435/$0.87 per 1M tokens it undercuts Amazon Nova Pro, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: DeepSeek V4 — Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs: DeepSeek V4 — 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 near-frontier coding at ~1/12 the cost: DeepSeek V4 — That is its strongest area.
An enterprise with regional data-residency rules: Amazon Nova Pro or DeepSeek V4 — Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
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.
DeepSeek V4: where it fits
China's open-weight price earthquake — near-frontier capability at roughly a twelfth of GPT-5.5's cost. Released April 24, 2026 by DeepSeek, it is built for near-frontier coding at ~1/12 the cost, open MIT-licensed weights you can self-host, no long-context surcharge, and highest LiveCodeBench result.
Its trade-offs: trails the very best on hardest agentic coding, and text/code focused, less multimodal. 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 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 DeepSeek V4 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 DeepSeek V4 leans toward near-frontier coding at ~1/12 the cost, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Amazon Nova Pro or DeepSeek V4?
DeepSeek V4 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?
DeepSeek V4 — 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 DeepSeek V4 together?
Yes — a multi-model platform like LumiChats gives you Amazon Nova Pro, DeepSeek V4 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 DeepSeek V4?
DeepSeek V4 — released April 24, 2026, about 17 months after Amazon Nova Pro.
Amazon Nova Pro vs DeepSeek V4
Amazon · US | DeepSeek · China · 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 DeepSeek V4 for near-frontier coding at ~1/12 the cost or open mit-licensed weights you can self-host. Choose DeepSeek V4 if you need self-hosting or data privacy; Amazon Nova Pro if you want a managed API.
Amazon Nova Pro (Amazon, US) and DeepSeek V4 (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 Pro is amazon's multimodal Bedrock model at $0.80/$3.20 with a 300K window — an enterprise-integrated generalist, not a frontier model. DeepSeek V4 is china's open-weight price earthquake — near-frontier capability at roughly a twelfth of GPT-5.5's cost. 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
▸Price: DeepSeek V4 is about 1.8× cheaper on input ($0.435/$0.87 per 1M tokens vs $0.8/$3.2 per 1M tokens) — modest, but it adds up at steady volume.
▸Context window: DeepSeek V4 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: DeepSeek V4 is the newer model by about 17 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 Pro
DeepSeek V4
Provider
Amazon (US)
DeepSeek (China)
Released
December 5, 2024
April 24, 2026
Context window
300K (~450 pages)
1M (~1,500 pages)
Price (in/out)
$0.8/$3.2 per 1M tokens
$0.435/$0.87 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, video, code
text, code
SWE-Bench Verified
Not published
80.6%
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
DeepSeek V4 is comparatively weak here — text/code focused, less multimodal
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; DeepSeek V4 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; DeepSeek V4 does not.
Near-frontier coding at ~1/12 the cost
DeepSeek V4
At $0.435/$0.87 per 1M tokens it undercuts Amazon Nova Pro ($0.8/$3.2 per 1M tokens), and that gap compounds at volume.
Open MIT-licensed weights you can self-host
DeepSeek V4
Open weights make this possible at all — Amazon Nova Pro is API-only, so it cannot leave the vendor's servers.
No long-context surcharge
DeepSeek V4
Its 1M window holds about 3.3× more than Amazon Nova Pro's 300K in a single prompt.
Lowest cost at scale
DeepSeek V4
At $0.435/$0.87 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
DeepSeek V4
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
→ DeepSeek V4
At $0.435/$0.87 per 1M tokens it undercuts Amazon Nova Pro, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ DeepSeek V4
Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ DeepSeek V4
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 near-frontier coding at ~1/12 the cost
→ DeepSeek V4
That is its strongest area.
An enterprise with regional data-residency rules
→ Amazon Nova Pro or DeepSeek V4
Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
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.
DeepSeek V4: where it fits
China's open-weight price earthquake — near-frontier capability at roughly a twelfth of GPT-5.5's cost. Released April 24, 2026 by DeepSeek, it is built for near-frontier coding at ~1/12 the cost, open MIT-licensed weights you can self-host, no long-context surcharge, and highest LiveCodeBench result.
Its trade-offs: trails the very best on hardest agentic coding, and text/code focused, less multimodal. 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 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 DeepSeek V4 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 DeepSeek V4 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 DeepSeek V4 leans toward near-frontier coding at ~1/12 the cost, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Amazon Nova Pro or DeepSeek V4?
DeepSeek V4 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?
DeepSeek V4 — 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 DeepSeek V4 together?
Yes — a multi-model platform like LumiChats gives you Amazon Nova Pro, DeepSeek V4 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 DeepSeek V4?
DeepSeek V4 — released April 24, 2026, about 17 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.