Pick Amazon Nova 2 Pro for amazon's next-generation nova flagship - a 1m-token context window with selectable reasoning effort or deep aws bedrock integration for teams already building on aws. Pick DeepSeek V3.2 for long-context efficiency via deepseek sparse attention (dsa) or agentic tool-use with thinking integrated into tool calls (thinking/non-thinking modes). Choose DeepSeek V3.2 if you need self-hosting or data privacy; Amazon Nova 2 Pro if you want a managed API.
Amazon Nova 2 Pro (Amazon, US) and DeepSeek V3.2 (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 2 Pro is amazon's next-generation Nova flagship - 1M context, selectable reasoning effort, and deep Bedrock integration, replacing the retiring Nova Premier. DeepSeek V3.2 is a cost-efficient, open-weight (MIT) 685B-parameter MoE model whose DeepSeek Sparse Attention delivers GPT-5-comparable reasoning with far cheaper long-context inference. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Price: DeepSeek V3.2 is about 7.8× cheaper on input ($0.28/$0.42 per 1M tokens vs $2.19/$17.5 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
Context window: Amazon Nova 2 Pro holds 7.6× more — 1M (~1,500 pages) vs 131K (~197 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
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 2 Pro
DeepSeek V3.2
Provider
Amazon (US)
DeepSeek (China)
Released
December 2, 2025
December 1, 2025
Context window
1M (~1,500 pages)
131K (~197 pages)
Price (in/out)
$2.19/$17.5 per 1M tokens
$0.28/$0.42 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image
text, code
SWE-Bench Verified
Not published
73.1%
MRCR v2 @ 1M
Not published
Not published
Who wins what
Amazon's next-generation Nova flagship - a 1M-token context window with selectable reasoning effort: Amazon Nova 2 Pro — Its 1M window holds about 7.6× more than DeepSeek V3.2's 131K in a single prompt.
Deep AWS Bedrock integration for teams already building on AWS: Amazon Nova 2 Pro — Amazon's next-generation Nova flagship - 1M context, selectable reasoning effort, and deep Bedrock integration, replacing the retiring Nova Premier — and it carries the larger 1M context.
A companion real-time-voice model (Nova 2 Sonic) in the same family: Amazon Nova 2 Pro — DeepSeek V3.2 is comparatively weak here — superseded - no longer listed on DeepSeek's current pricing page as of August 2026; DeepSeek V4-Flash/V4-Pro are the current models
Long-context efficiency via DeepSeek Sparse Attention (DSA): DeepSeek V3.2 — A cost-efficient, open-weight (MIT) 685B-parameter MoE model whose DeepSeek Sparse Attention delivers GPT-5-comparable reasoning with far cheaper long-context inference — and it runs cheaper at $0.28/$0.42 per 1M tokens.
Agentic tool-use with thinking integrated into tool calls (thinking/non-thinking modes): DeepSeek V3.2 — A cost-efficient, open-weight (MIT) 685B-parameter MoE model whose DeepSeek Sparse Attention delivers GPT-5-comparable reasoning with far cheaper long-context inference — and its weights are open while Amazon Nova 2 Pro is API-only.
Elite competition math and reasoning (AIME 2025 93.1, Codeforces 2386): DeepSeek V3.2 — DeepSeek V3.2 lists elite competition math and reasoning (AIME 2025 93.1, Codeforces 2386) among its strengths; Amazon Nova 2 Pro does not.
Lowest cost at scale: DeepSeek V3.2 — At $0.28/$0.42 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: Amazon Nova 2 Pro — Its 1M window is about 7.6× larger than DeepSeek V3.2's 131K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: DeepSeek V3.2 — At $0.28/$0.42 per 1M tokens it undercuts Amazon Nova 2 Pro, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Amazon Nova 2 Pro — Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs: DeepSeek V3.2 — Open weights let you run it on your own hardware; Amazon Nova 2 Pro is API-only.
Anyone whose priority is amazon's next-generation nova flagship - a 1m-token context window with selectable reasoning effort: Amazon Nova 2 Pro — It is specifically built for that.
Anyone whose priority is long-context efficiency via deepseek sparse attention (dsa): DeepSeek V3.2 — That is its strongest area.
An enterprise with regional data-residency rules: Amazon Nova 2 Pro or DeepSeek V3.2 — Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
Amazon Nova 2 Pro: where it fits
Amazon's next-generation Nova flagship - 1M context, selectable reasoning effort, and deep Bedrock integration, replacing the retiring Nova Premier. Released December 2, 2025 by Amazon, it is built for amazon's next-generation Nova flagship - a 1M-token context window with selectable reasoning effort, deep AWS Bedrock integration for teams already building on AWS, a companion real-time-voice model (Nova 2 Sonic) in the same family, and replaces the original Nova Premier, which AWS is retiring in September 2026.
Its trade-offs are real: pricing shown reflects preview-tier rates and may change at general availability, amazon's Nova line has historically scored below independent-intelligence leaders like Claude, GPT, and Gemini, and a newer release with less real-world production track record than established flagships. At $2.19 in / $17.5 out per million tokens, it sits in the mid price band.
DeepSeek V3.2: where it fits
A cost-efficient, open-weight (MIT) 685B-parameter MoE model whose DeepSeek Sparse Attention delivers GPT-5-comparable reasoning with far cheaper long-context inference. Released December 1, 2025 by DeepSeek, it is built for long-context efficiency via DeepSeek Sparse Attention (DSA), agentic tool-use with thinking integrated into tool calls (thinking/non-thinking modes), elite competition math and reasoning (AIME 2025 93.1, Codeforces 2386), and low-cost, open-weight (MIT) self-hosting.
Its trade-offs: superseded - no longer listed on DeepSeek's current pricing page as of August 2026; DeepSeek V4-Flash/V4-Pro are the current models, text-only — no image, audio, or video input, and sWE-Bench Verified (73.1) trails the top closed coding models (Claude 4.5 Sonnet 77.2, Gemini 3 Pro 76.2). At $0.28 in / $0.42 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 V3.2 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Amazon Nova 2 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 2 Pro or DeepSeek V3.2 better for coding?
Public SWE-Bench figures are not available for Amazon Nova 2 Pro, so the honest test is your own repository — run an identical real bug through both. By design, Amazon Nova 2 Pro leans toward amazon's next-generation nova flagship - a 1m-token context window with selectable reasoning effort while DeepSeek V3.2 leans toward long-context efficiency via deepseek sparse attention (dsa), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Amazon Nova 2 Pro or DeepSeek V3.2?
DeepSeek V3.2 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Amazon Nova 2 Pro is API-metered at $2.19/$17.5 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?
Amazon Nova 2 Pro — 1M vs 131K, about 7.6× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Amazon Nova 2 Pro and DeepSeek V3.2 together?
Yes — a multi-model platform like LumiChats gives you Amazon Nova 2 Pro, DeepSeek V3.2 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 2 Pro or DeepSeek V3.2?
Amazon Nova 2 Pro — released December 2, 2025, about 1 days after DeepSeek V3.2.
Amazon Nova 2 Pro vs DeepSeek V3.2
Amazon · US | DeepSeek · China · Updated June 2026
Quick verdict
Pick Amazon Nova 2 Pro for amazon's next-generation nova flagship - a 1m-token context window with selectable reasoning effort or deep aws bedrock integration for teams already building on aws. Pick DeepSeek V3.2 for long-context efficiency via deepseek sparse attention (dsa) or agentic tool-use with thinking integrated into tool calls (thinking/non-thinking modes). Choose DeepSeek V3.2 if you need self-hosting or data privacy; Amazon Nova 2 Pro if you want a managed API.
Amazon Nova 2 Pro (Amazon, US) and DeepSeek V3.2 (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 2 Pro is amazon's next-generation Nova flagship - 1M context, selectable reasoning effort, and deep Bedrock integration, replacing the retiring Nova Premier. DeepSeek V3.2 is a cost-efficient, open-weight (MIT) 685B-parameter MoE model whose DeepSeek Sparse Attention delivers GPT-5-comparable reasoning with far cheaper long-context inference. 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 V3.2 is about 7.8× cheaper on input ($0.28/$0.42 per 1M tokens vs $2.19/$17.5 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
▸Context window: Amazon Nova 2 Pro holds 7.6× more — 1M (~1,500 pages) vs 131K (~197 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸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 2 Pro
DeepSeek V3.2
Provider
Amazon (US)
DeepSeek (China)
Released
December 2, 2025
December 1, 2025
Context window
1M (~1,500 pages)
131K (~197 pages)
Price (in/out)
$2.19/$17.5 per 1M tokens
$0.28/$0.42 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image
text, code
SWE-Bench Verified
Not published
73.1%
MRCR v2 @ 1M
Not published
Not published
Who wins what
Amazon's next-generation Nova flagship - a 1M-token context window with selectable reasoning effort
Amazon Nova 2 Pro
Its 1M window holds about 7.6× more than DeepSeek V3.2's 131K in a single prompt.
Deep AWS Bedrock integration for teams already building on AWS
Amazon Nova 2 Pro
Amazon's next-generation Nova flagship - 1M context, selectable reasoning effort, and deep Bedrock integration, replacing the retiring Nova Premier — and it carries the larger 1M context.
A companion real-time-voice model (Nova 2 Sonic) in the same family
Amazon Nova 2 Pro
DeepSeek V3.2 is comparatively weak here — superseded - no longer listed on DeepSeek's current pricing page as of August 2026; DeepSeek V4-Flash/V4-Pro are the current models
Long-context efficiency via DeepSeek Sparse Attention (DSA)
DeepSeek V3.2
A cost-efficient, open-weight (MIT) 685B-parameter MoE model whose DeepSeek Sparse Attention delivers GPT-5-comparable reasoning with far cheaper long-context inference — and it runs cheaper at $0.28/$0.42 per 1M tokens.
Agentic tool-use with thinking integrated into tool calls (thinking/non-thinking modes)
DeepSeek V3.2
A cost-efficient, open-weight (MIT) 685B-parameter MoE model whose DeepSeek Sparse Attention delivers GPT-5-comparable reasoning with far cheaper long-context inference — and its weights are open while Amazon Nova 2 Pro is API-only.
Elite competition math and reasoning (AIME 2025 93.1, Codeforces 2386)
DeepSeek V3.2
DeepSeek V3.2 lists elite competition math and reasoning (AIME 2025 93.1, Codeforces 2386) among its strengths; Amazon Nova 2 Pro does not.
Lowest cost at scale
DeepSeek V3.2
At $0.28/$0.42 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
Amazon Nova 2 Pro
Its 1M window is about 7.6× larger than DeepSeek V3.2's 131K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ DeepSeek V3.2
At $0.28/$0.42 per 1M tokens it undercuts Amazon Nova 2 Pro, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Amazon Nova 2 Pro
Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ DeepSeek V3.2
Open weights let you run it on your own hardware; Amazon Nova 2 Pro is API-only.
Anyone whose priority is amazon's next-generation nova flagship - a 1m-token context window with selectable reasoning effort
→ Amazon Nova 2 Pro
It is specifically built for that.
Anyone whose priority is long-context efficiency via deepseek sparse attention (dsa)
→ DeepSeek V3.2
That is its strongest area.
An enterprise with regional data-residency rules
→ Amazon Nova 2 Pro or DeepSeek V3.2
Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
Amazon Nova 2 Pro: where it fits
Amazon's next-generation Nova flagship - 1M context, selectable reasoning effort, and deep Bedrock integration, replacing the retiring Nova Premier. Released December 2, 2025 by Amazon, it is built for amazon's next-generation Nova flagship - a 1M-token context window with selectable reasoning effort, deep AWS Bedrock integration for teams already building on AWS, a companion real-time-voice model (Nova 2 Sonic) in the same family, and replaces the original Nova Premier, which AWS is retiring in September 2026.
Its trade-offs are real: pricing shown reflects preview-tier rates and may change at general availability, amazon's Nova line has historically scored below independent-intelligence leaders like Claude, GPT, and Gemini, and a newer release with less real-world production track record than established flagships. At $2.19 in / $17.5 out per million tokens, it sits in the mid price band.
DeepSeek V3.2: where it fits
A cost-efficient, open-weight (MIT) 685B-parameter MoE model whose DeepSeek Sparse Attention delivers GPT-5-comparable reasoning with far cheaper long-context inference. Released December 1, 2025 by DeepSeek, it is built for long-context efficiency via DeepSeek Sparse Attention (DSA), agentic tool-use with thinking integrated into tool calls (thinking/non-thinking modes), elite competition math and reasoning (AIME 2025 93.1, Codeforces 2386), and low-cost, open-weight (MIT) self-hosting.
Its trade-offs: superseded - no longer listed on DeepSeek's current pricing page as of August 2026; DeepSeek V4-Flash/V4-Pro are the current models, text-only — no image, audio, or video input, and sWE-Bench Verified (73.1) trails the top closed coding models (Claude 4.5 Sonnet 77.2, Gemini 3 Pro 76.2). At $0.28 in / $0.42 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 V3.2 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Amazon Nova 2 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 2 Pro and DeepSeek V3.2 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 2 Pro or DeepSeek V3.2 better for coding?
Public SWE-Bench figures are not available for Amazon Nova 2 Pro, so the honest test is your own repository — run an identical real bug through both. By design, Amazon Nova 2 Pro leans toward amazon's next-generation nova flagship - a 1m-token context window with selectable reasoning effort while DeepSeek V3.2 leans toward long-context efficiency via deepseek sparse attention (dsa), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Amazon Nova 2 Pro or DeepSeek V3.2?
DeepSeek V3.2 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Amazon Nova 2 Pro is API-metered at $2.19/$17.5 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?
Amazon Nova 2 Pro — 1M vs 131K, about 7.6× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Amazon Nova 2 Pro and DeepSeek V3.2 together?
Yes — a multi-model platform like LumiChats gives you Amazon Nova 2 Pro, DeepSeek V3.2 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 2 Pro or DeepSeek V3.2?
Amazon Nova 2 Pro — released December 2, 2025, about 1 days after DeepSeek V3.2.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.