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 Qwen 3.7 Max for long-horizon agentic coding (swe-bench pro 60.6, terminal-bench 2.0 69.7) or 1m-token long-document and full-codebase analysis. On a tight budget at scale, Amazon Nova Pro is the value pick.
Amazon Nova Pro (Amazon, US) and Qwen 3.7 Max (Alibaba, 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. Qwen 3.7 Max is alibaba's agent-first frontier model — a 1M-token context and long-horizon coding at about half the cost of US flagships. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Price: Amazon Nova Pro is about 3.1× cheaper on input ($0.8/$3.2 per 1M tokens vs $2.5/$7.5 per 1M tokens) — meaningful once you are processing millions of tokens a month.
Context window: Qwen 3.7 Max 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: Qwen 3.7 Max is the newer model by about 18 months (released May 20, 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
Qwen 3.7 Max
Provider
Amazon (US)
Alibaba (China)
Released
December 5, 2024
May 20, 2026
Context window
300K (~450 pages)
1M (~1,500 pages)
Price (in/out)
$0.8/$3.2 per 1M tokens
$2.5/$7.5 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, video, code
text, code
SWE-Bench Verified
Not published
Not published
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 — Qwen 3.7 Max is comparatively weak here — text-only — no vision input (the Plus variant adds images)
Deep AWS and Bedrock integration for enterprise pipelines: Amazon Nova Pro — Amazon's multimodal Bedrock model at $0.80/$3.20 with a 300K window — an enterprise-integrated generalist, not a frontier model — and it runs cheaper at $0.8/$3.2 per 1M tokens.
Balanced cost-to-capability for general business tasks: Amazon Nova Pro — At $0.8/$3.2 per 1M tokens it undercuts Qwen 3.7 Max ($2.5/$7.5 per 1M tokens), and that gap compounds at volume.
Long-horizon agentic coding (SWE-Bench Pro 60.6, Terminal-Bench 2.0 69.7): Qwen 3.7 Max — Its 1M window holds about 3.3× more than Amazon Nova Pro's 300K in a single prompt.
1M-token long-document and full-codebase analysis: Qwen 3.7 Max — Alibaba's agent-first frontier model — a 1M-token context and long-horizon coding at about half the cost of US flagships — and it carries the larger 1M context.
MCP tool orchestration and multi-hour autonomous runs: Qwen 3.7 Max — Alibaba's agent-first frontier model — a 1M-token context and long-horizon coding at about half the cost of US flagships — and it is the newer of the two.
Lowest cost at scale: Amazon Nova Pro — At $0.8/$3.2 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: Qwen 3.7 Max — 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: Amazon Nova Pro — At $0.8/$3.2 per 1M tokens it undercuts Qwen 3.7 Max, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Qwen 3.7 Max — Larger 1M window fits more in one prompt.
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 long-horizon agentic coding (swe-bench pro 60.6, terminal-bench 2.0 69.7): Qwen 3.7 Max — That is its strongest area.
An enterprise with regional data-residency rules: Amazon Nova Pro or Qwen 3.7 Max — 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.
Qwen 3.7 Max: where it fits
Alibaba's agent-first frontier model — a 1M-token context and long-horizon coding at about half the cost of US flagships. Released May 20, 2026 by Alibaba, it is built for long-horizon agentic coding (SWE-Bench Pro 60.6, Terminal-Bench 2.0 69.7), 1M-token long-document and full-codebase analysis, mCP tool orchestration and multi-hour autonomous runs, and frontier intelligence at roughly half the price of US flagships.
Its trade-offs: text-only — no vision input (the Plus variant adds images), closed-weight, API-only — no self-hosting, trails GPT-5.5 and Claude Opus on the hardest one-shot reasoning, and chinese-jurisdiction data-residency considerations. At $2.5 in / $7.5 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
This is less "which is smarter" and more "which ecosystem fits." Amazon Nova Pro (US) and Qwen 3.7 Max (China) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Amazon Nova Pro is the cheaper option, which matters at volume. The pragmatic move is to run one real task through both and judge the outputs against your own constraints — including where your data is allowed to be processed.
Frequently asked questions
Is Amazon Nova Pro or Qwen 3.7 Max 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 Pro leans toward multimodal input across text, image and video at $0.80/$3.20 while Qwen 3.7 Max leans toward long-horizon agentic coding (swe-bench pro 60.6, terminal-bench 2.0 69.7), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Amazon Nova Pro or Qwen 3.7 Max?
Amazon Nova Pro is cheaper — $0.8/$3.2 per 1M tokens vs $2.5/$7.5 per 1M tokens, roughly 3.1× apart on input.
Which has the bigger context window?
Qwen 3.7 Max — 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 Qwen 3.7 Max together?
Yes — a multi-model platform like LumiChats gives you Amazon Nova Pro, Qwen 3.7 Max 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 Qwen 3.7 Max?
Qwen 3.7 Max — released May 20, 2026, about 18 months after Amazon Nova Pro.
Amazon Nova Pro vs Qwen 3.7 Max
Amazon · US | Alibaba · 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 Qwen 3.7 Max for long-horizon agentic coding (swe-bench pro 60.6, terminal-bench 2.0 69.7) or 1m-token long-document and full-codebase analysis. On a tight budget at scale, Amazon Nova Pro is the value pick.
Amazon Nova Pro (Amazon, US) and Qwen 3.7 Max (Alibaba, 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. Qwen 3.7 Max is alibaba's agent-first frontier model — a 1M-token context and long-horizon coding at about half the cost of US flagships. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Price: Amazon Nova Pro is about 3.1× cheaper on input ($0.8/$3.2 per 1M tokens vs $2.5/$7.5 per 1M tokens) — meaningful once you are processing millions of tokens a month.
▸Context window: Qwen 3.7 Max 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: Qwen 3.7 Max is the newer model by about 18 months (released May 20, 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
Qwen 3.7 Max
Provider
Amazon (US)
Alibaba (China)
Released
December 5, 2024
May 20, 2026
Context window
300K (~450 pages)
1M (~1,500 pages)
Price (in/out)
$0.8/$3.2 per 1M tokens
$2.5/$7.5 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, video, code
text, code
SWE-Bench Verified
Not published
Not published
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
Qwen 3.7 Max is comparatively weak here — text-only — no vision input (the Plus variant adds images)
Deep AWS and Bedrock integration for enterprise pipelines
Amazon Nova Pro
Amazon's multimodal Bedrock model at $0.80/$3.20 with a 300K window — an enterprise-integrated generalist, not a frontier model — and it runs cheaper at $0.8/$3.2 per 1M tokens.
Balanced cost-to-capability for general business tasks
Amazon Nova Pro
At $0.8/$3.2 per 1M tokens it undercuts Qwen 3.7 Max ($2.5/$7.5 per 1M tokens), and that gap compounds at volume.
Long-horizon agentic coding (SWE-Bench Pro 60.6, Terminal-Bench 2.0 69.7)
Qwen 3.7 Max
Its 1M window holds about 3.3× more than Amazon Nova Pro's 300K in a single prompt.
1M-token long-document and full-codebase analysis
Qwen 3.7 Max
Alibaba's agent-first frontier model — a 1M-token context and long-horizon coding at about half the cost of US flagships — and it carries the larger 1M context.
MCP tool orchestration and multi-hour autonomous runs
Qwen 3.7 Max
Alibaba's agent-first frontier model — a 1M-token context and long-horizon coding at about half the cost of US flagships — and it is the newer of the two.
Lowest cost at scale
Amazon Nova Pro
At $0.8/$3.2 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
Qwen 3.7 Max
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
→ Amazon Nova Pro
At $0.8/$3.2 per 1M tokens it undercuts Qwen 3.7 Max, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Qwen 3.7 Max
Larger 1M window fits more in one prompt.
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 long-horizon agentic coding (swe-bench pro 60.6, terminal-bench 2.0 69.7)
→ Qwen 3.7 Max
That is its strongest area.
An enterprise with regional data-residency rules
→ Amazon Nova Pro or Qwen 3.7 Max
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.
Qwen 3.7 Max: where it fits
Alibaba's agent-first frontier model — a 1M-token context and long-horizon coding at about half the cost of US flagships. Released May 20, 2026 by Alibaba, it is built for long-horizon agentic coding (SWE-Bench Pro 60.6, Terminal-Bench 2.0 69.7), 1M-token long-document and full-codebase analysis, mCP tool orchestration and multi-hour autonomous runs, and frontier intelligence at roughly half the price of US flagships.
Its trade-offs: text-only — no vision input (the Plus variant adds images), closed-weight, API-only — no self-hosting, trails GPT-5.5 and Claude Opus on the hardest one-shot reasoning, and chinese-jurisdiction data-residency considerations. At $2.5 in / $7.5 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
This is less "which is smarter" and more "which ecosystem fits." Amazon Nova Pro (US) and Qwen 3.7 Max (China) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Amazon Nova Pro is the cheaper option, which matters at volume. The pragmatic move is to run one real task through both and judge the outputs against your own constraints — including where your data is allowed to be processed.
Want both Amazon Nova Pro and Qwen 3.7 Max 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 Qwen 3.7 Max 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 Pro leans toward multimodal input across text, image and video at $0.80/$3.20 while Qwen 3.7 Max leans toward long-horizon agentic coding (swe-bench pro 60.6, terminal-bench 2.0 69.7), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Amazon Nova Pro or Qwen 3.7 Max?
Amazon Nova Pro is cheaper — $0.8/$3.2 per 1M tokens vs $2.5/$7.5 per 1M tokens, roughly 3.1× apart on input.
Which has the bigger context window?
Qwen 3.7 Max — 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 Qwen 3.7 Max together?
Yes — a multi-model platform like LumiChats gives you Amazon Nova Pro, Qwen 3.7 Max 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 Qwen 3.7 Max?
Qwen 3.7 Max — released May 20, 2026, about 18 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.