API cost decision in 10 seconds

Gemma 4 26B A4B (free) vs LFM2.5-1.2B-Thinking (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 26B A4B (free)
Sample savings$00%
10x traffic gap$0

Context-window winner: Gemma 4 26B A4B (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 pickGemma 4 26B A4B (free)LFM2.5-1.2B-Thinking (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 26B A4B (free) 262.14K vs 32.77K

Gemma 4 26B A4B (free) has 229.38K more context (8x 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.
Gemma 4 26B A4B (free) 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

both models tie on input price; both models tie on output price; Gemma 4 26B A4B (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 Gemma 4 26B A4B (free) and $0 for LFM2.5-1.2B-Thinking (free).

Best Fit

Choose Gemma 4 26B A4B (free) when you care most about larger context window.

Choose LFM2.5-1.2B-Thinking (free) when its provider, model quality, latency, or availability is more important than the numeric price/context winner.

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 26B A4B (free) has 229.38K more context (8x larger).
Head-to-Head Specs
FeatureGemma 4 26B A4B (free)
(Google)
LFM2.5-1.2B-Thinking (free)
(LiquidAI)
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 Window262.14K32.77K
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 26B A4B (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.

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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.

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Google catalog

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

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LiquidAI catalog

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

Open LiquidAI models
Gemma 4 26B A4B (free)

Gemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind. Despite 25.2B total parameters, only 3.8B activate per token during inference — delivering near-31B quality at...

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...