Nemotron 3 Nano Omni vs Qianfan-OCR-Fast
Nemotron 3 Nano Omni (2026) and Qianfan-OCR-Fast (2026) are compact production models from NVIDIA AI and Baidu AI. Nemotron 3 Nano Omni ships a 262k-token context window, while Qianfan-OCR-Fast ships a 66k-token context window. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads. It focuses on practical selection signals rather than broad model-family marketing.
Nemotron 3 Nano Omni fits 4x more tokens; pick it for long-context work and Qianfan-OCR-Fast for tighter calls.
Decision scorecard
Local evidence first| Signal | Nemotron 3 Nano Omni | Qianfan-OCR-Fast |
|---|---|---|
| Best for | multimodal apps | multimodal apps |
| Decision fit | Long context, Vision, and Classification | Vision |
| Context window | 262k | 66k |
| Cheapest output | - | $2.81/1M tokens |
| Provider routes | 1 tracked | 1 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Nemotron 3 Nano Omni has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Local decision data tags Nemotron 3 Nano Omni for Long context, Vision, and Classification.
- Qianfan-OCR-Fast uniquely exposes Vision in local model data.
- Local decision data tags Qianfan-OCR-Fast for Vision.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Nemotron 3 Nano Omni
Unavailable
No complete token price in local provider data
Qianfan-OCR-Fast
$1,247
Cheapest tracked route/tier: OpenRouter
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Qianfan-OCR-Fast adds Vision in local capability data.
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- Check replacement coverage for Vision before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-04-28 | 2026-04-20 |
| Context window | 262k | 66k |
| Parameters | 30B | — |
| Architecture | Hybrid Mamba-Transformer MoE | decoder only |
| License | NVIDIA Open Model | Proprietary |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Nemotron 3 Nano Omni | Qianfan-OCR-Fast |
|---|---|---|
| Input price | - | $0.68/1M tokens |
| Output price | - | $2.81/1M tokens |
| Providers |
Capabilities
| Capability | Nemotron 3 Nano Omni | Qianfan-OCR-Fast |
|---|---|---|
| Vision | No | Yes |
| Multimodal | Yes | Yes |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | No | No |
| Code execution | No | 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: Qianfan-OCR-Fast. Both models share multimodal input, 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.
Pricing coverage is uneven: Nemotron 3 Nano Omni has no token price sourced yet and Qianfan-OCR-Fast has $0.68/1M input tokens. Provider availability is 1 tracked routes versus 1. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Nemotron 3 Nano Omni when long-context analysis and larger context windows are central to the workload. Choose Qianfan-OCR-Fast when vision-heavy evaluation 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. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.
FAQ
Which has a larger context window, Nemotron 3 Nano Omni or Qianfan-OCR-Fast?
Nemotron 3 Nano Omni supports 262k tokens, while Qianfan-OCR-Fast supports 66k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is Nemotron 3 Nano Omni or Qianfan-OCR-Fast open source?
Nemotron 3 Nano Omni is listed under NVIDIA Open Model. Qianfan-OCR-Fast is listed under Proprietary. 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, Nemotron 3 Nano Omni or Qianfan-OCR-Fast?
Qianfan-OCR-Fast 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 multimodal input, Nemotron 3 Nano Omni or Qianfan-OCR-Fast?
Both Nemotron 3 Nano Omni and Qianfan-OCR-Fast expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Where can I run Nemotron 3 Nano Omni and Qianfan-OCR-Fast?
Nemotron 3 Nano Omni is available on OpenRouter. Qianfan-OCR-Fast is available on OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
When should I pick Nemotron 3 Nano Omni over Qianfan-OCR-Fast?
Nemotron 3 Nano Omni fits 4x more tokens; pick it for long-context work and Qianfan-OCR-Fast for tighter calls. If your workload also depends on long-context analysis, start with Nemotron 3 Nano Omni; if it depends on vision-heavy evaluation, run the same evaluation with Qianfan-OCR-Fast.
Continue comparing
Last reviewed: 2026-05-18. Data sourced from public model cards and provider documentation.