Amazon Nova Premier vs gpt-oss-120b

Amazon · US  |  OpenAI · US · Updated June 2026

Quick verdict

Pick Amazon Nova Premier for 1m-token context with deep aws bedrock integration or amazon's most capable nova model, positioned as a 'teacher' for distilling smaller models. Pick gpt-oss-120b for self-hostable on a single 80gb h100 gpu via mxfp4 or configurable reasoning depth (low/medium/high). Choose gpt-oss-120b if you need self-hosting or data privacy; Amazon Nova Premier if you want a managed API.

Amazon Nova Premier (Amazon) and gpt-oss-120b (OpenAI) are two of the models people most often weigh against each other in 2026. Amazon Nova Premier is amazon's flagship 1M-context Nova model on AWS Bedrock - a useful ecosystem anchor and distillation teacher, but weak and pricey on independent intelligence. gpt-oss-120b is openAI's open-weight 117B-parameter MoE reasoning model (5.1B active) that runs on a single 80GB GPU and approaches o4-mini on reasoning, coding, and tool use. 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

Side-by-side specs

SpecAmazon Nova Premiergpt-oss-120b
ProviderAmazon (US) OpenAI (US)
ReleasedApril 30, 2025 August 5, 2025
Context window1M (~1,500 pages) 131K (~197 pages)
Price (in/out)$2.5/$12.5 per 1M tokens Open weight (self-host / free)
Open weight?No — API only Yes — self-hostable
Modalitiestext, image text, code
SWE-Bench VerifiedNot published 62.4%
MRCR v2 @ 1MNot published Not published

Who wins what

1M-token context with deep AWS Bedrock integration

Amazon Nova Premier

Its 1M window holds about 7.6× more than gpt-oss-120b's 131K in a single prompt.

Amazon's most capable Nova model, positioned as a 'teacher' for distilling smaller models

Amazon Nova Premier

gpt-oss-120b is comparatively weak here — 131K context and 5.1B active params trail the largest frontier closed models

A natural fit for teams already building on AWS

Amazon Nova Premier

Amazon's flagship 1M-context Nova model on AWS Bedrock - a useful ecosystem anchor and distillation teacher, but weak and pricey on independent intelligence — and it carries the larger 1M context.

Self-hostable on a single 80GB H100 GPU via MXFP4

gpt-oss-120b

Open weights make this possible at all — Amazon Nova Premier is API-only, so it cannot leave the vendor's servers.

Configurable reasoning depth (low/medium/high)

gpt-oss-120b

OpenAI's open-weight 117B-parameter MoE reasoning model (5.1B active) that runs on a single 80GB GPU and approaches o4-mini on reasoning, coding, and tool use — and its weights are open while Amazon Nova Premier is API-only.

Agentic tool use, function calling, and code execution

gpt-oss-120b

OpenAI's open-weight 117B-parameter MoE reasoning model (5.1B active) that runs on a single 80GB GPU and approaches o4-mini on reasoning, coding, and tool use — and it is the newer of the two.

Lowest cost at scale

gpt-oss-120b

Its weights are open, so at volume you pay for your own hardware instead of Amazon Nova Premier's $2.5/$12.5 per 1M tokens.

Largest single-prompt input

Amazon Nova Premier

Its 1M window is about 7.6× larger than gpt-oss-120b's 131K, fitting roughly 1,500 pages in one prompt.

Which should you pick?

A cost-sensitive startup shipping high volume

gpt-oss-120b

At Open weight (self-host / free) it undercuts Amazon Nova Premier, and on millions of tokens that margin decides the monthly bill.

Someone analysing very long documents or codebases

Amazon Nova Premier

Larger 1M window fits more in one prompt.

A team with data-privacy or self-hosting needs

gpt-oss-120b

Open weights let you run it on your own hardware; Amazon Nova Premier is API-only.

Anyone whose priority is 1m-token context with deep aws bedrock integration

Amazon Nova Premier

It is specifically built for that.

Anyone whose priority is self-hostable on a single 80gb h100 gpu via mxfp4

gpt-oss-120b

That is its strongest area.

Amazon Nova Premier: where it fits

Amazon's flagship 1M-context Nova model on AWS Bedrock - a useful ecosystem anchor and distillation teacher, but weak and pricey on independent intelligence. Released April 30, 2025 by Amazon, it is built for 1M-token context with deep AWS Bedrock integration, amazon's most capable Nova model, positioned as a 'teacher' for distilling smaller models, a natural fit for teams already building on AWS, and multimodal input for complex reasoning across text and images.

Its trade-offs are real: weak on independent intelligence - Artificial Analysis Intelligence Index of 13, below average for its tier, expensive for its score at $2.50/$12.50 per million tokens, a 2025 model - older than the 2026 frontier it competes against, and sources disagree on modalities (Amazon cites image input; some evaluations list text-only). At $2.5 in / $12.5 out per million tokens, it sits in the mid price band.

gpt-oss-120b: where it fits

OpenAI's open-weight 117B-parameter MoE reasoning model (5.1B active) that runs on a single 80GB GPU and approaches o4-mini on reasoning, coding, and tool use. Released August 5, 2025 by OpenAI, it is built for self-hostable on a single 80GB H100 GPU via MXFP4, configurable reasoning depth (low/medium/high), agentic tool use, function calling, and code execution, and full chain-of-thought visibility for debugging.

Its trade-offs: text-only, no image, audio, or video input, and 131K context and 5.1B active params trail the largest frontier closed models. 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. gpt-oss-120b gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Amazon Nova Premier 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 Premier and gpt-oss-120b 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.

See pricing

Frequently asked questions

Is Amazon Nova Premier or gpt-oss-120b better for coding?

Public SWE-Bench figures are not available for Amazon Nova Premier, so the honest test is your own repository — run an identical real bug through both. By design, Amazon Nova Premier leans toward 1m-token context with deep aws bedrock integration while gpt-oss-120b leans toward self-hostable on a single 80gb h100 gpu via mxfp4, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, Amazon Nova Premier or gpt-oss-120b?

gpt-oss-120b is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Amazon Nova Premier is API-metered at $2.5/$12.5 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 Premier — 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 Premier and gpt-oss-120b together?

Yes — a multi-model platform like LumiChats gives you Amazon Nova Premier, gpt-oss-120b 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 Premier or gpt-oss-120b?

gpt-oss-120b — released August 5, 2025, about 3 months after Amazon Nova Premier.

Related comparisons

Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.