API cost decision in 10 seconds

NewNemotron 3 Nano Omni (free) vs Gemma 4 31B (free)

The standard workload cost is tied; choose by context window, provider fit, latency, or model quality.

Pricing data updated:  Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

The standard workload cost is tied; choose by context window, provider fit, latency, or model quality.

Both models are estimated at $0 for the standard 1M input plus 500K output workload.

Cost-first pickTie
Context-first pickGemma 4 31B (free)
Sample savings$00%
10x traffic gap$0

Context-window winner: Gemma 4 31B (free). Cost does not separate this pair on the standard workload, so the next decision point is context window and model behavior.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

The two models stay tied across the input-heavy, balanced, and output-heavy sample workloads.

Workload shapeToken mixBetter pickNemotron 3 Nano Omni (free)Gemma 4 31B (free)
Input-heavy / RAG5M input + 500K outputTie$0$0
Balanced workload1M input + 1M outputTie$0$0
Output-heavy chatbot1M input + 5M outputTie$0$0
Cheaper input Tie $0 vs $0 / 1M

Both models report the same input price at $0 per 1M tokens.

Cheaper output Tie $0 vs $0 / 1M

Both models report the same output price at $0 per 1M tokens.

Larger context Gemma 4 31B (free) 256K vs 262.14K

Gemma 4 31B (free) has 6.14K more context (1.02x larger).

Sample workload Tie $0 vs $0

Both models have the same estimated cost for the standard 1M input plus 500K output workload: $0.

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
Nemotron 3 Nano Omni (free) Calculating… Estimated API cost
Gemma 4 31B (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

both models tie on input price; both models tie on output price; Gemma 4 31B (free) offers the larger context window. For the 1M input plus 500K output sample, the standard workload cost is tied.

For a 1M input token plus 500K output token workload, the estimated API cost is $0 for Nemotron 3 Nano Omni (free) and $0 for Gemma 4 31B (free).

Best Fit

Choose Nemotron 3 Nano Omni (free) when its provider, model quality, latency, or availability is more important than the numeric price/context winner.

Choose Gemma 4 31B (free) when you care most about larger context window.

Decision Notes
  • Both models are estimated at $0 for the standard 1M input plus 500K output workload.
  • Both models have the same estimated cost for the standard 1M input plus 500K output workload: $0.
  • Both models report the same input price at $0 per 1M tokens.
  • Both models report the same output price at $0 per 1M tokens.
  • Gemma 4 31B (free) has 6.14K more context (1.02x larger).
Head-to-Head Specs
FeatureNewNemotron 3 Nano Omni (free)
(NVIDIA)
Gemma 4 31B (free)
(Google)
Input Price
prompt tokens per 1M
$0$0
Completion Price
per 1M tokens
$0$0
Sample Workload Cost
1M input + 500K output
$0$0
Context Window256K262.14K
Release Date

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionTieBoth models are estimated at $0 for the standard 1M input plus 500K output workload.
High-volume input processingTieLower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbotsTieLower output-token price matters most when assistants generate many completion tokens.
RAG or long-document workGemma 4 31B (free)A larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

Same-provider lower-cost swaps
  • No lower-cost same-provider swap is currently tracked for this pair.
Popular competitors
  • No popular competitor is currently available.

Cheaper alternatives

Review low-cost models sorted by a standard 1M input plus 500K output workload.

Open cheapest models

Larger context alternatives

Find models with larger context windows for RAG, long documents, and codebase review.

Open largest context models

Provider catalogs

Compare models within provider hubs before choosing a final API vendor.

Open provider hubs

NVIDIA catalog

Review all tracked NVIDIA models before deciding whether this matchup is the right shortlist.

Open NVIDIA models

Google catalog

Check other Google models with comparable pricing, context, or release timing.

Open Google models
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...

Gemma 4 31B (free)

Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output. Features a 256K token context window, configurable thinking/reasoning mode, native function...