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 Falcon-H1R 7B for tii says it outperforms models up to 7x its size (32b-47b class) on math/logic benchmarks, scoring 83.1% on aime 2025 (tii's own figures) or a hybrid transformer + mamba2 'high-density reasoning' design at just 7b parameters. Choose Falcon-H1R 7B if you need self-hosting or data privacy; Amazon Nova Pro if you want a managed API.
Amazon Nova Pro (Amazon, US) and Falcon-H1R 7B (Technology Innovation Institute, UAE) 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. Falcon-H1R 7B is tII's compact 7B reasoning model that claims to beat models many times its size on math and logic, fully open and free to self-host. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Cost model: Falcon-H1R 7B ships open weights you can self-host (hardware cost only, no per-token fee), while Amazon Nova Pro is API-metered at $0.8/$3.2 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
Context window: 300K vs 256K — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
Recency: Falcon-H1R 7B is the newer model by about 13 months (released January 5, 2026), usually meaning fresher training data and capabilities.
Ecosystem: this is a US-vs-UAE matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Specifications
Spec
Amazon Nova Pro
Falcon-H1R 7B
Provider
Amazon (US)
Technology Innovation Institute (UAE)
Released
December 5, 2024
January 5, 2026
Context window
300K (~450 pages)
256K (~393 pages)
Price (in/out)
$0.8/$3.2 per 1M tokens
Open weight (self-host / free)
Open weight?
No — API only
Yes — self-hostable
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 — Amazon Nova Pro lists multimodal input across text, image and video at $0.80/$3.20 among its strengths; Falcon-H1R 7B does not.
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; Falcon-H1R 7B does not.
Balanced cost-to-capability for general business tasks: Amazon Nova Pro — Falcon-H1R 7B is comparatively weak here — a specialist reasoning/math model, not a general-purpose frontier assistant
TII says it outperforms models up to 7x its size (32B-47B class) on math/logic benchmarks, scoring 83.1% on AIME 2025 (TII's own figures): Falcon-H1R 7B — TII's compact 7B reasoning model that claims to beat models many times its size on math and logic, fully open and free to self-host — and its weights are open while Amazon Nova Pro is API-only.
A hybrid Transformer + Mamba2 'high-density reasoning' design at just 7B parameters: Falcon-H1R 7B — Amazon Nova Pro is comparatively weak here — not a frontier reasoning or coding model against 2026 flagships
Native 256K context window despite its small size: Falcon-H1R 7B — TII's compact 7B reasoning model that claims to beat models many times its size on math and logic, fully open and free to self-host — and it is the newer of the two.
Lowest cost at scale: Falcon-H1R 7B — Its weights are open, so at volume you pay for your own hardware instead of Amazon Nova Pro's $0.8/$3.2 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume: Falcon-H1R 7B — At Open weight (self-host / free) it undercuts Amazon Nova Pro, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Amazon Nova Pro — Larger 300K window fits more in one prompt.
A team with data-privacy or self-hosting needs: Falcon-H1R 7B — 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 tii says it outperforms models up to 7x its size (32b-47b class) on math/logic benchmarks, scoring 83.1% on aime 2025 (tii's own figures): Falcon-H1R 7B — That is its strongest area.
An enterprise with regional data-residency rules: Amazon Nova Pro or Falcon-H1R 7B — Origin (US vs UAE) 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.
Falcon-H1R 7B: where it fits
TII's compact 7B reasoning model that claims to beat models many times its size on math and logic, fully open and free to self-host. Released January 5, 2026 by Technology Innovation Institute, it is built for tII says it outperforms models up to 7x its size (32B-47B class) on math/logic benchmarks, scoring 83.1% on AIME 2025 (TII's own figures), a hybrid Transformer + Mamba2 'high-density reasoning' design at just 7B parameters, native 256K context window despite its small size, and fully open under TII's permissive Falcon LLM License - free to self-host.
Its trade-offs: benchmark comparisons against much larger models are TII's own reported figures, not independently reproduced, a specialist reasoning/math model, not a general-purpose frontier assistant, and smaller ecosystem and less third-party tooling than mainstream open models like Llama or Qwen. 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. Falcon-H1R 7B 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 Falcon-H1R 7B 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 Falcon-H1R 7B leans toward tii says it outperforms models up to 7x its size (32b-47b class) on math/logic benchmarks, scoring 83.1% on aime 2025 (tii's own figures), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Amazon Nova Pro or Falcon-H1R 7B?
Falcon-H1R 7B 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?
Effectively neither — 300K vs 256K is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Amazon Nova Pro and Falcon-H1R 7B together?
Yes — a multi-model platform like LumiChats gives you Amazon Nova Pro, Falcon-H1R 7B 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 Falcon-H1R 7B?
Falcon-H1R 7B — released January 5, 2026, about 13 months after Amazon Nova Pro.
Amazon Nova Pro vs Falcon-H1R 7B
Amazon · US | Technology Innovation Institute · UAE · 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 Falcon-H1R 7B for tii says it outperforms models up to 7x its size (32b-47b class) on math/logic benchmarks, scoring 83.1% on aime 2025 (tii's own figures) or a hybrid transformer + mamba2 'high-density reasoning' design at just 7b parameters. Choose Falcon-H1R 7B if you need self-hosting or data privacy; Amazon Nova Pro if you want a managed API.
Amazon Nova Pro (Amazon, US) and Falcon-H1R 7B (Technology Innovation Institute, UAE) 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. Falcon-H1R 7B is tII's compact 7B reasoning model that claims to beat models many times its size on math and logic, fully open and free to self-host. 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
▸Cost model: Falcon-H1R 7B ships open weights you can self-host (hardware cost only, no per-token fee), while Amazon Nova Pro is API-metered at $0.8/$3.2 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
▸Context window: 300K vs 256K — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
▸Recency: Falcon-H1R 7B is the newer model by about 13 months (released January 5, 2026), usually meaning fresher training data and capabilities.
▸Ecosystem: this is a US-vs-UAE matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
Spec
Amazon Nova Pro
Falcon-H1R 7B
Provider
Amazon (US)
Technology Innovation Institute (UAE)
Released
December 5, 2024
January 5, 2026
Context window
300K (~450 pages)
256K (~393 pages)
Price (in/out)
$0.8/$3.2 per 1M tokens
Open weight (self-host / free)
Open weight?
No — API only
Yes — self-hostable
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
Amazon Nova Pro lists multimodal input across text, image and video at $0.80/$3.20 among its strengths; Falcon-H1R 7B does not.
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; Falcon-H1R 7B does not.
Balanced cost-to-capability for general business tasks
Amazon Nova Pro
Falcon-H1R 7B is comparatively weak here — a specialist reasoning/math model, not a general-purpose frontier assistant
TII says it outperforms models up to 7x its size (32B-47B class) on math/logic benchmarks, scoring 83.1% on AIME 2025 (TII's own figures)
Falcon-H1R 7B
TII's compact 7B reasoning model that claims to beat models many times its size on math and logic, fully open and free to self-host — and its weights are open while Amazon Nova Pro is API-only.
A hybrid Transformer + Mamba2 'high-density reasoning' design at just 7B parameters
Falcon-H1R 7B
Amazon Nova Pro is comparatively weak here — not a frontier reasoning or coding model against 2026 flagships
Native 256K context window despite its small size
Falcon-H1R 7B
TII's compact 7B reasoning model that claims to beat models many times its size on math and logic, fully open and free to self-host — and it is the newer of the two.
Lowest cost at scale
Falcon-H1R 7B
Its weights are open, so at volume you pay for your own hardware instead of Amazon Nova Pro's $0.8/$3.2 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Falcon-H1R 7B
At Open weight (self-host / free) it undercuts Amazon Nova Pro, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Amazon Nova Pro
Larger 300K window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ Falcon-H1R 7B
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 tii says it outperforms models up to 7x its size (32b-47b class) on math/logic benchmarks, scoring 83.1% on aime 2025 (tii's own figures)
→ Falcon-H1R 7B
That is its strongest area.
An enterprise with regional data-residency rules
→ Amazon Nova Pro or Falcon-H1R 7B
Origin (US vs UAE) 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.
Falcon-H1R 7B: where it fits
TII's compact 7B reasoning model that claims to beat models many times its size on math and logic, fully open and free to self-host. Released January 5, 2026 by Technology Innovation Institute, it is built for tII says it outperforms models up to 7x its size (32B-47B class) on math/logic benchmarks, scoring 83.1% on AIME 2025 (TII's own figures), a hybrid Transformer + Mamba2 'high-density reasoning' design at just 7B parameters, native 256K context window despite its small size, and fully open under TII's permissive Falcon LLM License - free to self-host.
Its trade-offs: benchmark comparisons against much larger models are TII's own reported figures, not independently reproduced, a specialist reasoning/math model, not a general-purpose frontier assistant, and smaller ecosystem and less third-party tooling than mainstream open models like Llama or Qwen. 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. Falcon-H1R 7B 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 Falcon-H1R 7B 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 Falcon-H1R 7B 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 Falcon-H1R 7B leans toward tii says it outperforms models up to 7x its size (32b-47b class) on math/logic benchmarks, scoring 83.1% on aime 2025 (tii's own figures), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Amazon Nova Pro or Falcon-H1R 7B?
Falcon-H1R 7B 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?
Effectively neither — 300K vs 256K is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Amazon Nova Pro and Falcon-H1R 7B together?
Yes — a multi-model platform like LumiChats gives you Amazon Nova Pro, Falcon-H1R 7B 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 Falcon-H1R 7B?
Falcon-H1R 7B — released January 5, 2026, about 13 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.