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 Muse Spark 1.1 for scaled tool use — 88.1 on mcp atlas, ahead of opus 4.8 and gpt-5.5 (vendor-reported) or subagent orchestration — trained to run as a main agent or a subagent that escalates when stuck. On a tight budget at scale, Amazon Nova Pro is the value pick.
Amazon Nova Pro (Amazon) and Muse Spark 1.1 (Meta) are two of the models people most often weigh against each other in 2026. 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. Muse Spark 1.1 is meta's first paid, closed-weight frontier model — class-leading agentic tool use at a quarter of rivals' price, but it trails on coding. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Price: Amazon Nova Pro is about 1.6× cheaper on input ($0.8/$3.2 per 1M tokens vs $1.25/$4.25 per 1M tokens) — modest, but it adds up at steady volume.
Context window: Muse Spark 1.1 holds 3.5× more — 1M (~1,573 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: Muse Spark 1.1 is the newer model by about 19 months (released July 9, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Amazon Nova Pro
Muse Spark 1.1
Provider
Amazon (US)
Meta (US)
Released
December 5, 2024
July 9, 2026
Context window
300K (~450 pages)
1M (~1,573 pages)
Price (in/out)
$0.8/$3.2 per 1M tokens
$1.25/$4.25 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, video, code
text, image, video, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
54.1%
Who wins what
Multimodal input across text, image and video at $0.80/$3.20: 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.
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; Muse Spark 1.1 does not.
Balanced cost-to-capability for general business tasks: Amazon Nova Pro — At $0.8/$3.2 per 1M tokens it undercuts Muse Spark 1.1 ($1.25/$4.25 per 1M tokens), and that gap compounds at volume.
Scaled tool use — 88.1 on MCP Atlas, ahead of Opus 4.8 and GPT-5.5 (vendor-reported): Muse Spark 1.1 — Meta's first paid, closed-weight frontier model — class-leading agentic tool use at a quarter of rivals' price, but it trails on coding — and it carries the larger 1M context.
Subagent orchestration — trained to run as a main agent or a subagent that escalates when stuck: Muse Spark 1.1 — Meta's first paid, closed-weight frontier model — class-leading agentic tool use at a quarter of rivals' price, but it trails on coding — and it is the newer of the two.
Professional agentic work — 54.7 on JobBench, a wide margin over rivals (vendor-reported): Muse Spark 1.1 — Muse Spark 1.1 lists professional agentic work — 54.7 on JobBench, a wide margin over rivals (vendor-reported) among its strengths; Amazon Nova Pro does not.
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: Muse Spark 1.1 — Its 1M window is about 3.5× larger than Amazon Nova Pro's 300K, fitting roughly 1,573 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 Muse Spark 1.1, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Muse Spark 1.1 — 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 scaled tool use — 88.1 on mcp atlas, ahead of opus 4.8 and gpt-5.5 (vendor-reported): Muse Spark 1.1 — That is its strongest area.
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.
Muse Spark 1.1: where it fits
Meta's first paid, closed-weight frontier model — class-leading agentic tool use at a quarter of rivals' price, but it trails on coding. Released July 9, 2026 by Meta, it is built for scaled tool use — 88.1 on MCP Atlas, ahead of Opus 4.8 and GPT-5.5 (vendor-reported), subagent orchestration — trained to run as a main agent or a subagent that escalates when stuck, professional agentic work — 54.7 on JobBench, a wide margin over rivals (vendor-reported), and managing its own context: it compacts the 1M window mid-run instead of relying on external windowing.
Its trade-offs: not the coding leader its launch framing implied — Meta's own report concedes it trails Opus 4.8 and GPT-5.5 on every coding benchmark, the 1M window oversells its recall: 54.1 on MRCR v2 at 1M against GPT-5.5's 74.0, closed weights end the free, self-hostable Llama path — this is the first model Meta has charged for, and uS-only public preview behind a waitlist, and every benchmark is vendor-reported with no third-party replication. At $1.25 in / $4.25 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
Amazon Nova Pro and Muse Spark 1.1 overlap enough that the right pick depends on your specific job. Amazon Nova Pro costs less per token; Muse Spark 1.1 holds the larger context; and each leads in its own area — Amazon Nova Pro for multimodal input across text, image and video at $0.80/$3.20, Muse Spark 1.1 for scaled tool use — 88.1 on mcp atlas, ahead of opus 4.8 and gpt-5.5 (vendor-reported). Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is Amazon Nova Pro or Muse Spark 1.1 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 Muse Spark 1.1 leans toward scaled tool use — 88.1 on mcp atlas, ahead of opus 4.8 and gpt-5.5 (vendor-reported), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Amazon Nova Pro or Muse Spark 1.1?
Amazon Nova Pro is cheaper — $0.8/$3.2 per 1M tokens vs $1.25/$4.25 per 1M tokens, roughly 1.6× apart on input.
Which has the bigger context window?
Muse Spark 1.1 — 1M vs 300K, about 3.5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Amazon Nova Pro and Muse Spark 1.1 together?
Yes — a multi-model platform like LumiChats gives you Amazon Nova Pro, Muse Spark 1.1 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 Muse Spark 1.1?
Muse Spark 1.1 — released July 9, 2026, about 19 months after Amazon Nova Pro.
Amazon Nova Pro vs Muse Spark 1.1
Amazon · US | Meta · US · 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 Muse Spark 1.1 for scaled tool use — 88.1 on mcp atlas, ahead of opus 4.8 and gpt-5.5 (vendor-reported) or subagent orchestration — trained to run as a main agent or a subagent that escalates when stuck. On a tight budget at scale, Amazon Nova Pro is the value pick.
Amazon Nova Pro (Amazon) and Muse Spark 1.1 (Meta) are two of the models people most often weigh against each other in 2026. 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. Muse Spark 1.1 is meta's first paid, closed-weight frontier model — class-leading agentic tool use at a quarter of rivals' price, but it trails on coding. 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 1.6× cheaper on input ($0.8/$3.2 per 1M tokens vs $1.25/$4.25 per 1M tokens) — modest, but it adds up at steady volume.
▸Context window: Muse Spark 1.1 holds 3.5× more — 1M (~1,573 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: Muse Spark 1.1 is the newer model by about 19 months (released July 9, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Amazon Nova Pro
Muse Spark 1.1
Provider
Amazon (US)
Meta (US)
Released
December 5, 2024
July 9, 2026
Context window
300K (~450 pages)
1M (~1,573 pages)
Price (in/out)
$0.8/$3.2 per 1M tokens
$1.25/$4.25 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, video, code
text, image, video, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
54.1%
Who wins what
Multimodal input across text, image and video at $0.80/$3.20
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.
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; Muse Spark 1.1 does not.
Balanced cost-to-capability for general business tasks
Amazon Nova Pro
At $0.8/$3.2 per 1M tokens it undercuts Muse Spark 1.1 ($1.25/$4.25 per 1M tokens), and that gap compounds at volume.
Scaled tool use — 88.1 on MCP Atlas, ahead of Opus 4.8 and GPT-5.5 (vendor-reported)
Muse Spark 1.1
Meta's first paid, closed-weight frontier model — class-leading agentic tool use at a quarter of rivals' price, but it trails on coding — and it carries the larger 1M context.
Subagent orchestration — trained to run as a main agent or a subagent that escalates when stuck
Muse Spark 1.1
Meta's first paid, closed-weight frontier model — class-leading agentic tool use at a quarter of rivals' price, but it trails on coding — and it is the newer of the two.
Professional agentic work — 54.7 on JobBench, a wide margin over rivals (vendor-reported)
Muse Spark 1.1
Muse Spark 1.1 lists professional agentic work — 54.7 on JobBench, a wide margin over rivals (vendor-reported) among its strengths; Amazon Nova Pro does not.
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
Muse Spark 1.1
Its 1M window is about 3.5× larger than Amazon Nova Pro's 300K, fitting roughly 1,573 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 Muse Spark 1.1, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Muse Spark 1.1
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 scaled tool use — 88.1 on mcp atlas, ahead of opus 4.8 and gpt-5.5 (vendor-reported)
→ Muse Spark 1.1
That is its strongest area.
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.
Muse Spark 1.1: where it fits
Meta's first paid, closed-weight frontier model — class-leading agentic tool use at a quarter of rivals' price, but it trails on coding. Released July 9, 2026 by Meta, it is built for scaled tool use — 88.1 on MCP Atlas, ahead of Opus 4.8 and GPT-5.5 (vendor-reported), subagent orchestration — trained to run as a main agent or a subagent that escalates when stuck, professional agentic work — 54.7 on JobBench, a wide margin over rivals (vendor-reported), and managing its own context: it compacts the 1M window mid-run instead of relying on external windowing.
Its trade-offs: not the coding leader its launch framing implied — Meta's own report concedes it trails Opus 4.8 and GPT-5.5 on every coding benchmark, the 1M window oversells its recall: 54.1 on MRCR v2 at 1M against GPT-5.5's 74.0, closed weights end the free, self-hostable Llama path — this is the first model Meta has charged for, and uS-only public preview behind a waitlist, and every benchmark is vendor-reported with no third-party replication. At $1.25 in / $4.25 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
Amazon Nova Pro and Muse Spark 1.1 overlap enough that the right pick depends on your specific job. Amazon Nova Pro costs less per token; Muse Spark 1.1 holds the larger context; and each leads in its own area — Amazon Nova Pro for multimodal input across text, image and video at $0.80/$3.20, Muse Spark 1.1 for scaled tool use — 88.1 on mcp atlas, ahead of opus 4.8 and gpt-5.5 (vendor-reported). Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Amazon Nova Pro and Muse Spark 1.1 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 Muse Spark 1.1 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 Muse Spark 1.1 leans toward scaled tool use — 88.1 on mcp atlas, ahead of opus 4.8 and gpt-5.5 (vendor-reported), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Amazon Nova Pro or Muse Spark 1.1?
Amazon Nova Pro is cheaper — $0.8/$3.2 per 1M tokens vs $1.25/$4.25 per 1M tokens, roughly 1.6× apart on input.
Which has the bigger context window?
Muse Spark 1.1 — 1M vs 300K, about 3.5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Amazon Nova Pro and Muse Spark 1.1 together?
Yes — a multi-model platform like LumiChats gives you Amazon Nova Pro, Muse Spark 1.1 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 Muse Spark 1.1?
Muse Spark 1.1 — released July 9, 2026, about 19 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.