API cost decision in 10 seconds

Gemma 4 31B vs Gemini 2.0 Flash

Pick Gemini 2.0 Flash when budget and context both matter.

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

Budget verdict

Pick Gemini 2.0 Flash when budget and context both matter.

On the standard 1M input plus 500K output workload, Gemini 2.0 Flash is estimated at $0.3 vs $0.3 for Gemma 4 31B, saving $0.005 (1.6% lower).

Cost-first pickGemini 2.0 Flash
Context-first pickGemini 2.0 Flash
Sample savings$0.0051.6%
10x traffic gap$0.05

Gemini 2.0 Flash is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $0.05. 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 Gemini 2.0 Flash, balanced workload favors Gemma 4 31B, and output-heavy chatbot favors Gemma 4 31B.

Workload shapeToken mixBetter pickGemma 4 31BGemini 2.0 Flash
Input-heavy / RAG5M input + 500K outputGemini 2.0 Flash$0.78$0.7
Balanced workload1M input + 1M outputGemma 4 31B$0.49$0.5
Output-heavy chatbot1M input + 5M outputGemma 4 31B$1.97$2.1
Cheaper input Gemini 2.0 Flash $0.12 vs $0.1 / 1M

Gemini 2.0 Flash is $0.02 cheaper per 1M input tokens (16.7% lower; 1.2x difference).

Cheaper output Gemma 4 31B $0.37 vs $0.4 / 1M

Gemma 4 31B is $0.03 cheaper per 1M output tokens (7.5% lower; 1.08x difference).

Larger context Gemini 2.0 Flash 262.14K vs 1M

Gemini 2.0 Flash has 737.86K more context (3.81x larger).

Sample workload Gemini 2.0 Flash $0.3 vs $0.3

Gemini 2.0 Flash is $0.005 cheaper on the standard workload (1.6% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
Gemma 4 31B Calculating… Estimated API cost
Gemini 2.0 Flash 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

Gemini 2.0 Flash has the lower input price; Gemma 4 31B has the lower output price; Gemini 2.0 Flash offers the larger context window. For the 1M input plus 500K output sample, Gemini 2.0 Flash 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 $0.3 for Gemini 2.0 Flash.

Best Fit

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

Choose Gemini 2.0 Flash when you care most about lower input-token price, and larger context window.

Decision Notes
  • On the standard 1M input plus 500K output workload, Gemini 2.0 Flash is estimated at $0.3 vs $0.3 for Gemma 4 31B, saving $0.005 (1.6% lower).
  • Gemini 2.0 Flash is $0.005 cheaper on the standard workload (1.6% lower).
  • Gemini 2.0 Flash is $0.02 cheaper per 1M input tokens (16.7% lower; 1.2x difference).
  • Gemma 4 31B is $0.03 cheaper per 1M output tokens (7.5% lower; 1.08x difference).
  • Gemini 2.0 Flash has 737.86K more context (3.81x larger).
Head-to-Head Specs
FeatureGemma 4 31B
(Google)
Gemini 2.0 Flash
(Google)
Input Price
prompt tokens per 1M
$0.12$0.1
Completion Price
per 1M tokens
$0.37$0.4
Sample Workload Cost
1M input + 500K output
$0.3$0.3
Context Window262.14K1M
Release Date
Popularity#27#46

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionGemini 2.0 FlashOn the standard 1M input plus 500K output workload, Gemini 2.0 Flash is estimated at $0.3 vs $0.3 for Gemma 4 31B, saving $0.005 (1.6% lower).
High-volume input processingGemini 2.0 FlashLower 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 workGemini 2.0 FlashA 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

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
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...

Gemini 2.0 Flash

Gemini Flash 2.0 offers a significantly faster time to first token (TTFT) compared to [Gemini Flash 1.5](/google/gemini-flash-1.5), while maintaining quality on par with larger models like [Gemini Pro 1.5](/google/gemini-pro-1.5). It...