API cost decision in 10 seconds

Gemma 4 31B vs Nemotron 3 Super

Pick Nemotron 3 Super when budget is the priority.

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

Budget verdict

Pick Nemotron 3 Super when budget is the priority.

On the standard 1M input plus 500K output workload, Nemotron 3 Super is estimated at $0.3 vs $0.4 for Gemma 4 31B, saving $0.1 (23.8% lower).

Cost-first pickNemotron 3 Super
Context-first pickBoth models
Sample savings$0.123.8%
10x traffic gap$0.95

The reported context window is tied, so cost and provider fit carry more weight. At 10x that traffic, the same price gap is about $0.95. 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 Nemotron 3 Super, and output-heavy chatbot favors Gemma 4 31B.

Workload shapeToken mixBetter pickGemma 4 31BNemotron 3 Super
Input-heavy / RAG5M input + 500K outputNemotron 3 Super$1.2$0.62
Balanced workload1M input + 1M outputNemotron 3 Super$0.6$0.53
Output-heavy chatbot1M input + 5M outputGemma 4 31B$2.2$2.33
Cheaper input Nemotron 3 Super $0.2 vs $0.08 / 1M

Nemotron 3 Super is $0.12 cheaper per 1M input tokens (60% lower; 2.5x difference).

Cheaper output Gemma 4 31B $0.4 vs $0.45 / 1M

Gemma 4 31B is $0.05 cheaper per 1M output tokens (11.1% lower; 1.12x difference).

Larger context Tie 262.14K vs 262.14K

Both models report the same context window at 262.14K tokens.

Sample workload Nemotron 3 Super $0.4 vs $0.3

Nemotron 3 Super is $0.1 cheaper on the standard workload (23.8% 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; both models report the same context window. For the 1M input plus 500K output sample, Nemotron 3 Super is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $0.4 for Gemma 4 31B and $0.3 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.

Decision Notes
  • On the standard 1M input plus 500K output workload, Nemotron 3 Super is estimated at $0.3 vs $0.4 for Gemma 4 31B, saving $0.1 (23.8% lower).
  • Nemotron 3 Super is $0.1 cheaper on the standard workload (23.8% lower).
  • Nemotron 3 Super is $0.12 cheaper per 1M input tokens (60% lower; 2.5x difference).
  • Gemma 4 31B is $0.05 cheaper per 1M output tokens (11.1% lower; 1.12x difference).
  • Both models report the same context window at 262.14K tokens.
Head-to-Head Specs
FeatureGemma 4 31B
(Google)
Nemotron 3 Super
(NVIDIA)
Input Price
prompt tokens per 1M
$0.2$0.08
Completion Price
per 1M tokens
$0.4$0.45
Sample Workload Cost
1M input + 500K output
$0.4$0.3
Context Window262.14K262.14K
Release Date

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionNemotron 3 SuperOn the standard 1M input plus 500K output workload, Nemotron 3 Super is estimated at $0.3 vs $0.4 for Gemma 4 31B, saving $0.1 (23.8% 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 workTieA larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

Same-provider lower-cost swaps
Larger context near this budget
  • Llama 4 Scout offers 1.31M context with $0.47 sample workload cost.
  • MiMo-V2.6-Flash offers 1.05M context with $0.28 sample workload cost.
  • GPT-6 Luna offers 1.05M context with $0.35 sample workload cost.
  • GPT-6 Luna Pro offers 1.05M context with $0.35 sample workload cost.

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

Google catalog

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

Open Google models

NVIDIA catalog

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

Open NVIDIA models
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...