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 Laguna XS 2.1 for remarkable efficiency — 70.9% on swe-bench verified from only 3b active parameters or open weights under openmdw-1.1, shipped day one in bf16, fp8, nvfp4 and int4 across every major runtime. Choose Laguna XS 2.1 if you need self-hosting or data privacy; Amazon Nova Pro if you want a managed API.
Amazon Nova Pro (Amazon) and Laguna XS 2.1 (Poolside) 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. Laguna XS 2.1 is a 33B open-weight coding MoE running on 3B active parameters — 70.9% SWE-Bench Verified and very cheap, but unproven. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Price: Laguna XS 2.1 is about 8× cheaper on input ($0.1/$0.2 per 1M tokens vs $0.8/$3.2 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
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: Laguna XS 2.1 is the newer model by about 19 months (released July 2, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Amazon Nova Pro
Laguna XS 2.1
Provider
Amazon (US)
Poolside (US)
Released
December 5, 2024
July 2, 2026
Context window
300K (~450 pages)
256K (~393 pages)
Price (in/out)
$0.8/$3.2 per 1M tokens
$0.1/$0.2 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, video, code
text, code
SWE-Bench Verified
Not published
70.9%
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 — Laguna XS 2.1 is comparatively weak here — the free endpoint trains on your inputs and outputs — disqualifying for proprietary code, which is its main use case
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; Laguna XS 2.1 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; Laguna XS 2.1 does not.
Remarkable efficiency — 70.9% on SWE-Bench Verified from only 3B active parameters: Laguna XS 2.1 — Amazon Nova Pro is comparatively weak here — no published SWE-Bench Verified score
Open weights under OpenMDW-1.1, shipped day one in BF16, FP8, NVFP4 and INT4 across every major runtime: Laguna XS 2.1 — Open weights make this possible at all — Amazon Nova Pro is API-only, so it cannot leave the vendor's servers.
Cheap even on the paid tier, at roughly a sixth of GLM 4.7's input price: Laguna XS 2.1 — At $0.1/$0.2 per 1M tokens it undercuts Amazon Nova Pro ($0.8/$3.2 per 1M tokens), and that gap compounds at volume.
Lowest cost at scale: Laguna XS 2.1 — At $0.1/$0.2 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Which should you pick?
A cost-sensitive startup shipping high volume: Laguna XS 2.1 — At $0.1/$0.2 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: Amazon Nova Pro — Larger 300K window fits more in one prompt.
A team with data-privacy or self-hosting needs: Laguna XS 2.1 — 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 remarkable efficiency — 70.9% on swe-bench verified from only 3b active parameters: Laguna XS 2.1 — 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.
Laguna XS 2.1: where it fits
A 33B open-weight coding MoE running on 3B active parameters — 70.9% SWE-Bench Verified and very cheap, but unproven. Released July 2, 2026 by Poolside, it is built for remarkable efficiency — 70.9% on SWE-Bench Verified from only 3B active parameters, open weights under OpenMDW-1.1, shipped day one in BF16, FP8, NVFP4 and INT4 across every major runtime, cheap even on the paid tier, at roughly a sixth of GLM 4.7's input price, and unusually transparent evaluation — it publishes its harness, step limits, and sandbox specs.
Its trade-offs: weeks old with no independent replication; every published score traces back to Poolside's own harness, the free endpoint trains on your inputs and outputs — disqualifying for proprietary code, which is its main use case, and weak on harder agentic work (37.5 on Terminal-Bench 2.0), and its gain over XS.2 is barely above noise. At $0.1 in / $0.2 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. Laguna XS 2.1 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 Laguna XS 2.1 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 Laguna XS 2.1 leans toward remarkable efficiency — 70.9% on swe-bench verified from only 3b active parameters, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Amazon Nova Pro or Laguna XS 2.1?
Laguna XS 2.1 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 Laguna XS 2.1 together?
Yes — a multi-model platform like LumiChats gives you Amazon Nova Pro, Laguna XS 2.1 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 Laguna XS 2.1?
Laguna XS 2.1 — released July 2, 2026, about 19 months after Amazon Nova Pro.
Amazon Nova Pro vs Laguna XS 2.1
Amazon · US | Poolside · 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 Laguna XS 2.1 for remarkable efficiency — 70.9% on swe-bench verified from only 3b active parameters or open weights under openmdw-1.1, shipped day one in bf16, fp8, nvfp4 and int4 across every major runtime. Choose Laguna XS 2.1 if you need self-hosting or data privacy; Amazon Nova Pro if you want a managed API.
Amazon Nova Pro (Amazon) and Laguna XS 2.1 (Poolside) 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. Laguna XS 2.1 is a 33B open-weight coding MoE running on 3B active parameters — 70.9% SWE-Bench Verified and very cheap, but unproven. 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: Laguna XS 2.1 is about 8× cheaper on input ($0.1/$0.2 per 1M tokens vs $0.8/$3.2 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
▸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: Laguna XS 2.1 is the newer model by about 19 months (released July 2, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Amazon Nova Pro
Laguna XS 2.1
Provider
Amazon (US)
Poolside (US)
Released
December 5, 2024
July 2, 2026
Context window
300K (~450 pages)
256K (~393 pages)
Price (in/out)
$0.8/$3.2 per 1M tokens
$0.1/$0.2 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, video, code
text, code
SWE-Bench Verified
Not published
70.9%
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
Laguna XS 2.1 is comparatively weak here — the free endpoint trains on your inputs and outputs — disqualifying for proprietary code, which is its main use case
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; Laguna XS 2.1 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; Laguna XS 2.1 does not.
Remarkable efficiency — 70.9% on SWE-Bench Verified from only 3B active parameters
Laguna XS 2.1
Amazon Nova Pro is comparatively weak here — no published SWE-Bench Verified score
Open weights under OpenMDW-1.1, shipped day one in BF16, FP8, NVFP4 and INT4 across every major runtime
Laguna XS 2.1
Open weights make this possible at all — Amazon Nova Pro is API-only, so it cannot leave the vendor's servers.
Cheap even on the paid tier, at roughly a sixth of GLM 4.7's input price
Laguna XS 2.1
At $0.1/$0.2 per 1M tokens it undercuts Amazon Nova Pro ($0.8/$3.2 per 1M tokens), and that gap compounds at volume.
Lowest cost at scale
Laguna XS 2.1
At $0.1/$0.2 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Laguna XS 2.1
At $0.1/$0.2 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
→ Amazon Nova Pro
Larger 300K window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ Laguna XS 2.1
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 remarkable efficiency — 70.9% on swe-bench verified from only 3b active parameters
→ Laguna XS 2.1
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.
Laguna XS 2.1: where it fits
A 33B open-weight coding MoE running on 3B active parameters — 70.9% SWE-Bench Verified and very cheap, but unproven. Released July 2, 2026 by Poolside, it is built for remarkable efficiency — 70.9% on SWE-Bench Verified from only 3B active parameters, open weights under OpenMDW-1.1, shipped day one in BF16, FP8, NVFP4 and INT4 across every major runtime, cheap even on the paid tier, at roughly a sixth of GLM 4.7's input price, and unusually transparent evaluation — it publishes its harness, step limits, and sandbox specs.
Its trade-offs: weeks old with no independent replication; every published score traces back to Poolside's own harness, the free endpoint trains on your inputs and outputs — disqualifying for proprietary code, which is its main use case, and weak on harder agentic work (37.5 on Terminal-Bench 2.0), and its gain over XS.2 is barely above noise. At $0.1 in / $0.2 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. Laguna XS 2.1 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 Laguna XS 2.1 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 Laguna XS 2.1 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 Laguna XS 2.1 leans toward remarkable efficiency — 70.9% on swe-bench verified from only 3b active parameters, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Amazon Nova Pro or Laguna XS 2.1?
Laguna XS 2.1 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 Laguna XS 2.1 together?
Yes — a multi-model platform like LumiChats gives you Amazon Nova Pro, Laguna XS 2.1 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 Laguna XS 2.1?
Laguna XS 2.1 — released July 2, 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.