GPT-5.3-Codex vs Nemotron-Nano-9B-v2
GPT-5.3-Codex (2026) and Nemotron-Nano-9B-v2 (2025) compare a coding-specialized model against a standalone API model. GPT-5.3-Codex ships a 400k-token context window, while Nemotron-Nano-9B-v2 ships a not-yet-sourced context window. On pricing, Nemotron-Nano-9B-v2 costs $0.04/1M input tokens versus $1.75/1M for the alternative. This page treats the result as workflow and deployment fit, not a universal model winner.
Treat this as a product-type comparison: GPT-5.3-Codex is coding-specialized model, while Nemotron-Nano-9B-v2 is standalone API model. Choose based on workflow fit before reading any benchmark or price row as decisive.
Decision scorecard
Local evidence first| Signal | GPT-5.3-Codex | Nemotron-Nano-9B-v2 |
|---|---|---|
| Product type | Coding-specialized model | Standalone API model |
| Best for | custom coding agents, code generation, and tool loops | provider-routed production |
| Decision fit | Coding, RAG, and Agents | Classification and JSON / Tool use |
| Context window | 400k | — |
| Cheapest output | $14/1M tokens | $0.16/1M tokens |
| Provider routes | 3 tracked | 3 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- GPT-5.3-Codex has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GPT-5.3-Codex uniquely exposes Vision, Reasoning, and Function calling in local model data.
- Local decision data tags GPT-5.3-Codex for Coding, RAG, and Agents.
- Nemotron-Nano-9B-v2 has the lower cheapest tracked output price at $0.16/1M tokens.
- Local decision data tags Nemotron-Nano-9B-v2 for Classification and JSON / Tool use.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
GPT-5.3-Codex
$4,900
Cheapest tracked route/tier: OpenRouter
Nemotron-Nano-9B-v2
$72.00
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $4,828. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter and Vercel AI Gateway; start route-level A/B tests there.
- Nemotron-Nano-9B-v2 is $13.84/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision, Reasoning, and Function calling before moving production traffic.
- Provider overlap exists on OpenRouter and Vercel AI Gateway; start route-level A/B tests there.
- GPT-5.3-Codex is $13.84/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- GPT-5.3-Codex adds Vision, Reasoning, and Function calling in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-02-05 | 2025-08-18 |
| Context window | 400k | — |
| Parameters | — | 9B |
| Architecture | decoder only | decoder only |
| License | Proprietary | Llama 3 Community |
| Openness | Proprietary | Open weights |
| Commercial use | Commercial use with conditions | Commercial use with conditions |
| Knowledge cutoff | 2025-08 | 2025-03 |
Pricing and availability
| Pricing attribute | GPT-5.3-Codex | Nemotron-Nano-9B-v2 |
|---|---|---|
| Input price | $1.75/1M tokens | $0.04/1M tokens |
| Output price | $14/1M tokens | $0.16/1M tokens |
| Providers |
Capabilities
| Capability | GPT-5.3-Codex | Nemotron-Nano-9B-v2 |
|---|---|---|
| Vision | Yes | No |
| Multimodal | No | No |
| Reasoning | Yes | No |
| Function calling | Yes | No |
| Tool use | Yes | No |
| Structured outputs | Yes | Yes |
| Code execution | Yes | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on vision: GPT-5.3-Codex, reasoning mode: GPT-5.3-Codex, function calling: GPT-5.3-Codex, tool use: GPT-5.3-Codex, and code execution: GPT-5.3-Codex. Both models share structured outputs, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, GPT-5.3-Codex lists $1.75/1M input and $14/1M output tokens on the cheapest tracked provider, while Nemotron-Nano-9B-v2 lists $0.04/1M input and $0.16/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Nemotron-Nano-9B-v2 lower by about $5.35 per million blended tokens. Availability is 3 providers versus 3, so concentration risk also matters.
Choose GPT-5.3-Codex when coding workflow support are central to the workload. Choose Nemotron-Nano-9B-v2 when provider fit and lower input-token cost are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency.
FAQ
Which is cheaper, GPT-5.3-Codex or Nemotron-Nano-9B-v2?
Nemotron-Nano-9B-v2 is cheaper on tracked token pricing. GPT-5.3-Codex costs $1.75/1M input and $14/1M output tokens. Nemotron-Nano-9B-v2 costs $0.04/1M input and $0.16/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is GPT-5.3-Codex or Nemotron-Nano-9B-v2 open source?
GPT-5.3-Codex is listed under Proprietary. Nemotron-Nano-9B-v2 is listed under Llama 3 Community. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for vision, GPT-5.3-Codex or Nemotron-Nano-9B-v2?
GPT-5.3-Codex has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for reasoning mode, GPT-5.3-Codex or Nemotron-Nano-9B-v2?
GPT-5.3-Codex has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for function calling, GPT-5.3-Codex or Nemotron-Nano-9B-v2?
GPT-5.3-Codex has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run GPT-5.3-Codex and Nemotron-Nano-9B-v2?
GPT-5.3-Codex is available on OpenRouter, OpenAI API, and Vercel AI Gateway. Nemotron-Nano-9B-v2 is available on NVIDIA NIM, OpenRouter, and Vercel AI Gateway. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.