API cost decision in 10 seconds

Gemma 4 31B vs Nemotron 3 Super

Pick Gemma 4 31B for lower cost; pick Nemotron 3 Super only if the larger context window matters more.

Page updated:  Data confirmed:  Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick Gemma 4 31B for lower cost; pick Nemotron 3 Super only if the larger context window matters more.

On the standard 1M input plus 500K output workload, Gemma 4 31B is estimated at $0.3 vs $0.32 for Nemotron 3 Super, saving $0.01 (3.2% lower).

Cost-first pickGemma 4 31B
Context-first pickNemotron 3 Super
Sample savings$0.013.2%
10x traffic gap$0.1

Nemotron 3 Super has more context, but Gemma 4 31B saves $0.01 on the standard workload. At 10x that traffic, the same price gap is about $0.1. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Cost winner changes by workload shape: input-heavy / RAG favors Nemotron 3 Super, balanced workload favors Gemma 4 31B, and output-heavy chatbot favors Gemma 4 31B.

Workload shapeToken mixBetter pickGemma 4 31BNemotron 3 Super
Input-heavy / RAG5M input + 500K outputNemotron 3 Super$0.78$0.68
Balanced workload1M input + 1M outputGemma 4 31B$0.49$0.54
Output-heavy chatbot1M input + 5M outputGemma 4 31B$1.97$2.34
Cheaper input Nemotron 3 Super $0.12 vs $0.09 / 1M

Nemotron 3 Super is $0.03 cheaper per 1M input tokens (25% lower; 1.33x difference).

Cheaper output Gemma 4 31B $0.37 vs $0.45 / 1M

Gemma 4 31B is $0.08 cheaper per 1M output tokens (17.8% lower; 1.22x difference).

Larger context Nemotron 3 Super 262.14K vs 1M

Nemotron 3 Super has 737.86K more context (3.81x larger).

Sample workload Gemma 4 31B $0.3 vs $0.32

Gemma 4 31B is $0.01 cheaper on the standard workload (3.2% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
Gemma 4 31B Calculating… Estimated API cost
Nemotron 3 Super 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 Super has the lower input price; Gemma 4 31B has the lower output price; Nemotron 3 Super offers the larger context window. For the 1M input plus 500K output sample, Gemma 4 31B is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $0.3 for Gemma 4 31B and $0.32 for Nemotron 3 Super.

Best Fit

Choose Gemma 4 31B when you care most about lower output-token price.

Choose Nemotron 3 Super when you care most about lower input-token price, and larger context window.

Decision Notes
  • On the standard 1M input plus 500K output workload, Gemma 4 31B is estimated at $0.3 vs $0.32 for Nemotron 3 Super, saving $0.01 (3.2% lower).
  • Gemma 4 31B is $0.01 cheaper on the standard workload (3.2% lower).
  • Nemotron 3 Super is $0.03 cheaper per 1M input tokens (25% lower; 1.33x difference).
  • Gemma 4 31B is $0.08 cheaper per 1M output tokens (17.8% lower; 1.22x difference).
  • Nemotron 3 Super has 737.86K more context (3.81x larger).
Head-to-Head Specs
FeatureGemma 4 31B
(Google)
Nemotron 3 Super
(NVIDIA)
Input Price
prompt tokens per 1M
$0.12$0.09
Completion Price
per 1M tokens
$0.37$0.45
Sample Workload Cost
1M input + 500K output
$0.3$0.32
Context Window262.14K1M
Release Date

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionGemma 4 31BOn the standard 1M input plus 500K output workload, Gemma 4 31B is estimated at $0.3 vs $0.32 for Nemotron 3 Super, saving $0.01 (3.2% lower).
High-volume input processingNemotron 3 SuperLower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbotsGemma 4 31BLower output-token price matters most when assistants generate many completion tokens.
RAG or long-document workNemotron 3 SuperA larger context window leaves more room for retrieved passages, conversation history, or source files.

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Larger context alternatives

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Provider catalogs

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

Open provider hubs

Google catalog

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NVIDIA catalog

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

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Gemma 4 31B

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...

Nemotron 3 Super

NVIDIA Nemotron 3 Super is a 120B-parameter open hybrid MoE model, activating just 12B parameters for maximum compute efficiency and accuracy in complex multi-agent applications. Built on a hybrid Mamba-Transformer...