API cost decision in 10 seconds

DeepSeek V3.1 vs NewNemotron 3 Nano Omni (free)

Pick Nemotron 3 Nano Omni (free) when budget and context both matter.

Page updated: 2026-05-26T15:08:08Z Data confirmed: 2026-05-26T18:08:02Z Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick Nemotron 3 Nano Omni (free) when budget and context both matter.

On the standard 1M input plus 500K output workload, Nemotron 3 Nano Omni (free) is estimated at $0 vs $0.6 for DeepSeek V3.1, saving $0.6 (100% lower).

Cost-first pickNemotron 3 Nano Omni (free)

Context-first pickNemotron 3 Nano Omni (free)

Sample savings$0.6100%

10x traffic gap$6.05

Nemotron 3 Nano Omni (free) is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $6.05. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Nemotron 3 Nano Omni (free) stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shape	Token mix	Better pick	DeepSeek V3.1	Nemotron 3 Nano Omni (free)
Input-heavy / RAG	5M input + 500K output	Nemotron 3 Nano Omni (free)	$1.45	$0
Balanced workload	1M input + 1M output	Nemotron 3 Nano Omni (free)	$1	$0
Output-heavy chatbot	1M input + 5M output	Nemotron 3 Nano Omni (free)	$4.16	$0

Cheaper input Nemotron 3 Nano Omni (free) $0.21 vs $0 / 1M

Nemotron 3 Nano Omni (free) is free for input tokens while DeepSeek V3.1 costs $0.21 per 1M tokens.

Cheaper output Nemotron 3 Nano Omni (free) $0.79 vs $0 / 1M

Nemotron 3 Nano Omni (free) is free for output tokens while DeepSeek V3.1 costs $0.79 per 1M tokens.

Larger context Nemotron 3 Nano Omni (free) 163.84K vs 256K

Nemotron 3 Nano Omni (free) has 92.16K more context (1.56x larger).

Sample workload Nemotron 3 Nano Omni (free) $0.6 vs $0

Nemotron 3 Nano Omni (free) is free for the standard workload while the other model is estimated at $0.6.

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.

Monthly input tokens Monthly output tokens

DeepSeek V3.1 Calculating… Estimated API cost

Nemotron 3 Nano Omni (free) Calculating… Estimated API cost

Cheaper for this workload Calculating… Difference: calculating…

This estimate uses normalized public API pricing per 1M tokens. It is a planning aid, not a billing quote. Verify provider pricing, limits, and terms before production use.

Quick Decision

Verdict

Nemotron 3 Nano Omni (free) has the lower input price; Nemotron 3 Nano Omni (free) has the lower output price; Nemotron 3 Nano Omni (free) offers the larger context window. For the 1M input plus 500K output sample, Nemotron 3 Nano Omni (free) is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $0.6 for DeepSeek V3.1 and $0 for Nemotron 3 Nano Omni (free).

Best Fit

Choose DeepSeek V3.1 when its provider, model quality, latency, or availability is more important than the numeric price/context winner.

Choose Nemotron 3 Nano Omni (free) when you care most about lower input-token price, lower output-token price, and larger context window.

Decision Notes

On the standard 1M input plus 500K output workload, Nemotron 3 Nano Omni (free) is estimated at $0 vs $0.6 for DeepSeek V3.1, saving $0.6 (100% lower).
Nemotron 3 Nano Omni (free) is free for the standard workload while the other model is estimated at $0.6.
Nemotron 3 Nano Omni (free) is free for input tokens while DeepSeek V3.1 costs $0.21 per 1M tokens.
Nemotron 3 Nano Omni (free) is free for output tokens while DeepSeek V3.1 costs $0.79 per 1M tokens.
Nemotron 3 Nano Omni (free) has 92.16K more context (1.56x larger).

Head-to-Head Specs

Feature	DeepSeek V3.1 (DeepSeek)	NewNemotron 3 Nano Omni (free) (NVIDIA)
Input Price prompt tokens per 1M	$0.21	$0
Completion Price per 1M tokens	$0.79	$0
Sample Workload Cost 1M input + 500K output	$0.6	$0
Context Window	163.84K	256K
Release Date	2025-08-21	2026-04-28
Popularity	#59	#96

Use-Case Decision Matrix

Use case	Better pick	Why
Budget-constrained production	Nemotron 3 Nano Omni (free)	On the standard 1M input plus 500K output workload, Nemotron 3 Nano Omni (free) is estimated at $0 vs $0.6 for DeepSeek V3.1, saving $0.6 (100% lower).
High-volume input processing	Nemotron 3 Nano Omni (free)	Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbots	Nemotron 3 Nano Omni (free)	Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document work	Nemotron 3 Nano Omni (free)	A larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

Same-provider lower-cost swaps

DeepSeek V4 Flash (free) can replace DeepSeek V3.1 when lower sample workload cost matters most: $0.
DeepSeek V4 Flash can replace DeepSeek V3.1 when lower sample workload cost matters most: $0.2.
R1 Distill Qwen 32B can replace DeepSeek V3.1 when lower sample workload cost matters most: $0.43.
DeepSeek V3.2 can replace DeepSeek V3.1 when lower sample workload cost matters most: $0.44.

Larger context near this budget

Llama 4 Scout offers 10M context with $0.23 sample workload cost.
Owl Alpha offers 1.05M context with $0 sample workload cost.
DeepSeek V4 Flash offers 1.05M context with $0.2 sample workload cost.
Gemini 2.5 Flash Lite offers 1.05M context with $0.3 sample workload cost.

Popular competitors

DeepSeek V4 Flash · DeepSeek · #1
Hy3 preview · Tencent · #2
Claude Opus 4.7 · Anthropic · #3
Claude Sonnet 4.6 · Anthropic · #4

Cheaper alternatives

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Provider catalogs

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DeepSeek catalog

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NVIDIA catalog

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DeepSeek V3.1

DeepSeek-V3.1 is a large hybrid reasoning model (671B parameters, 37B active) that supports both thinking and non-thinking modes via prompt templates. It extends the DeepSeek-V3 base with a two-phase long-context...

Nemotron 3 Nano Omni (free)

NVIDIA Nemotron™ 3 Nano Omni is a 30B-A3B open multimodal model designed to function as a perception and context sub-agent in enterprise agent systems. It accepts text, image, video, and...