API cost decision in 10 seconds

Gemma 4 31B vs LFM2.5-1.2B-Thinking (free)

Pick LFM2.5-1.2B-Thinking (free) for lower cost; pick Gemma 4 31B only if the larger context window matters more.

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

Budget verdict

Pick LFM2.5-1.2B-Thinking (free) for lower cost; pick Gemma 4 31B only if the larger context window matters more.

On the standard 1M input plus 500K output workload, LFM2.5-1.2B-Thinking (free) is estimated at $0 vs $0.3 for Gemma 4 31B, saving $0.3 (100% lower).

Cost-first pickLFM2.5-1.2B-Thinking (free)
Context-first pickGemma 4 31B
Sample savings$0.3100%
10x traffic gap$3.05

Gemma 4 31B has more context, but LFM2.5-1.2B-Thinking (free) saves $0.3 on the standard workload. At 10x that traffic, the same price gap is about $3.05. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

LFM2.5-1.2B-Thinking (free) stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shapeToken mixBetter pickGemma 4 31BLFM2.5-1.2B-Thinking (free)
Input-heavy / RAG5M input + 500K outputLFM2.5-1.2B-Thinking (free)$0.78$0
Balanced workload1M input + 1M outputLFM2.5-1.2B-Thinking (free)$0.49$0
Output-heavy chatbot1M input + 5M outputLFM2.5-1.2B-Thinking (free)$1.97$0
Cheaper input LFM2.5-1.2B-Thinking (free) $0.12 vs $0 / 1M

LFM2.5-1.2B-Thinking (free) is free for input tokens while Gemma 4 31B costs $0.12 per 1M tokens.

Cheaper output LFM2.5-1.2B-Thinking (free) $0.37 vs $0 / 1M

LFM2.5-1.2B-Thinking (free) is free for output tokens while Gemma 4 31B costs $0.37 per 1M tokens.

Larger context Gemma 4 31B 262.14K vs 32.77K

Gemma 4 31B has 229.38K more context (8x larger).

Sample workload LFM2.5-1.2B-Thinking (free) $0.3 vs $0

LFM2.5-1.2B-Thinking (free) is free for the standard workload while the other model is estimated at $0.3.

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
Gemma 4 31B Calculating… Estimated API cost
LFM2.5-1.2B-Thinking (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

LFM2.5-1.2B-Thinking (free) has the lower input price; LFM2.5-1.2B-Thinking (free) has the lower output price; Gemma 4 31B offers the larger context window. For the 1M input plus 500K output sample, LFM2.5-1.2B-Thinking (free) 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 for LFM2.5-1.2B-Thinking (free).

Best Fit

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

Choose LFM2.5-1.2B-Thinking (free) when you care most about lower input-token price, and lower output-token price.

Decision Notes
  • On the standard 1M input plus 500K output workload, LFM2.5-1.2B-Thinking (free) is estimated at $0 vs $0.3 for Gemma 4 31B, saving $0.3 (100% lower).
  • LFM2.5-1.2B-Thinking (free) is free for the standard workload while the other model is estimated at $0.3.
  • LFM2.5-1.2B-Thinking (free) is free for input tokens while Gemma 4 31B costs $0.12 per 1M tokens.
  • LFM2.5-1.2B-Thinking (free) is free for output tokens while Gemma 4 31B costs $0.37 per 1M tokens.
  • Gemma 4 31B has 229.38K more context (8x larger).
Head-to-Head Specs
FeatureGemma 4 31B
(Google)
LFM2.5-1.2B-Thinking (free)
(LiquidAI)
Input Price
prompt tokens per 1M
$0.12$0
Completion Price
per 1M tokens
$0.37$0
Sample Workload Cost
1M input + 500K output
$0.3$0
Context Window262.14K32.77K
Release Date

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionLFM2.5-1.2B-Thinking (free)On the standard 1M input plus 500K output workload, LFM2.5-1.2B-Thinking (free) is estimated at $0 vs $0.3 for Gemma 4 31B, saving $0.3 (100% lower).
High-volume input processingLFM2.5-1.2B-Thinking (free)Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbotsLFM2.5-1.2B-Thinking (free)Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document workGemma 4 31BA 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

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Google catalog

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LiquidAI catalog

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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...

LFM2.5-1.2B-Thinking (free)

LFM2.5-1.2B-Thinking is a lightweight reasoning-focused model optimized for agentic tasks, data extraction, and RAG—while still running comfortably on edge devices. It supports long context (up to 32K tokens) and is...