A 550B orchestrator against OpenAI's small, fast open reasoner.
Nemotron 3 Ultra and GPT-OSS 120B are both text-only reasoning models with tool support and zero-retention terms. Nemotron is the heavyweight orchestrator; GPT-OSS is the light, fast reasoner that costs a quarter as much.
Nemotron 3 Ultra has 550B parameters, 55B active per token, a 262k window and a $2.40 price. GPT-OSS 120B has 117B parameters, only 5B active, a 128k window and a $0.60 price. The trade is capacity and context against speed and cost.
At a glance
| Spec | Nemotron 3 Ultra | GPT-OSS 120B |
|---|---|---|
| Maker | NVIDIA | OpenAI |
| Parameters | 550B | 117B |
| Active per token | 55B | 5B |
| Context window | 262k (200,000 words) | 128k (95,000 words) |
| Upstream price / MTok | $2.40 | $0.60 |
| Image and video input | No | No |
| Tool use | Yes | Yes |
| Zero data retention | Yes | Yes |
| License | NVIDIA Open Model License | Apache 2.0 |
| Good at | Reasoning and orchestration | Reasoning and agent work |
Where Nemotron 3 Ultra pulls ahead
- Twice the context window at 262k tokens versus 128k, for longer reasoning traces and documents.
- More capacity for orchestrating other models and planning multi-step work.
- 55B active parameters per token when a problem needs heavier deliberation.
Where GPT-OSS 120B pulls ahead
- Price: $0.60 versus $2.40 per million tokens, four times cheaper.
- Only 5B active parameters per token, so it is fast and cheap for tool-heavy agent loops.
- OpenAI's open-weight reasoner, with a smaller and simpler deployment footprint.
The price difference
Nemotron 3 Ultra costs $2.40 per million tokens against $0.60 for GPT-OSS 120B — about 4.0x more. On UsingOpen you can chat with both for free inside the daily limit, so the rate is a fair proxy for how expensive each model is to run rather than a bill you pay here. Multiply it by your monthly token volume if you are comparing API access elsewhere.
Which should you choose?
GPT-OSS 120B is the better default for most reasoning and agent work: four times cheaper, much faster per token, and still capable of step-by-step tool use. The 128k window is the limit to watch.
Nemotron 3 Ultra earns its price when the task needs a larger orchestrator or a 262k context. Use it for long planning traces and multi-model coordination; use GPT-OSS for the tight, repeated loops.
Chat with Nemotron 3 Ultra free · Chat with GPT-OSS 120B free
Frequently asked questions
Which has the larger context window, Nemotron 3 Ultra or GPT-OSS 120B?
Nemotron 3 Ultra is listed at 262k (200,000 words); GPT-OSS 120B is listed at 128k (95,000 words). Nemotron 3 Ultra can hold more in one conversation, which matters for long codebases, archives and multi-hour agent runs.
Can Nemotron 3 Ultra or GPT-OSS 120B read images?
Neither model accepts images — both are text-only. A visual task needs a multimodal model such as Qwen3.8 Flash, GLM 5.3 Flash or Gemma 4 instead.
Is GPT-OSS 120B or Nemotron 3 Ultra better for coding?
GPT-OSS 120B is the closer fit for code here — the catalog tunes it for reasoning and agent work — while Nemotron 3 Ultra is aimed at reasoning and orchestration. For project-scale coding, start with GPT-OSS 120B; if the task leans toward the other model's strengths, it may still win.
Which is cheaper, Nemotron 3 Ultra or GPT-OSS 120B?
GPT-OSS 120B is listed at $0.60 per million tokens against $2.40 for Nemotron 3 Ultra — about 4.0x cheaper. Both are free to chat with on UsingOpen inside the daily limit when live; the rates matter if you are comparing what API access would cost.
Can I chat with Nemotron 3 Ultra and GPT-OSS 120B for free?
Yes. Both are selectable on UsingOpen without an account when they are live, and each user gets 10 free prompts per day. A model paused for capacity is unavailable until it returns; the picker shows live status. History stays on your device, and Compare mode can send one prompt to both models side by side.
Which is better for agent orchestration?
Nemotron 3 Ultra is positioned for reasoning and orchestration, with more parameters, a 262k window and 55B active per token. GPT-OSS 120B is the cheaper, faster option for smaller tool loops. Both support tools, so benchmark the actual workflow rather than assuming the bigger model wins.
Do either of these models read images?
No. Both are text-only. A visual task needs a multimodal model such as Qwen3.8 Flash, GLM 5.3 Flash or Gemma 4 instead.
Related comparisons
- GPT-OSS 120B vs DeepSeek V4 Flash — OpenAI's open-weight reasoner against DeepSeek's long-context bargain.
- Qwen3.8 2.4T vs Kimi K3 — The two trillion-parameter flagships: Qwen's text heavyweight against Kimi's multimodal giant.
- GLM 5.2 vs GLM 5.3 — Two generations of Z.ai's long-work model, with a price gap and a capacity catch.