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Gemma 4 26B A4B vs Llama 4 Maverick

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Gemma 4 26B A4B and Llama 4 Maverick.

Google

Gemma 4 26B A4B

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 โ€” delivering near-31B quality at...

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Meta

Llama 4 Maverick

Llama 4 Maverick 17B Instruct (128E) is a high-capacity multimodal language model from Meta, built on a mixture-of-experts (MoE) architecture with 128 experts and 17 billion active parameters per forward...

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Technical Specifications

SpecificationGemma 4 26B A4BLlama 4 Maverick
ProviderGoogleMeta
Context Window262,144 tokens1,048,576 tokens
Agent SuitabilityN/AN/A
Time to First Token (TTFT)N/AN/A
Deployment Modelmanaged apiself hostable
Production Stabilitystablebeta
API AvailableYesYes
Released Date2026-04-032025-04-05

API Pricing Comparison

Input Price per Million Tokens

Gemma 4 26B A4B

$0.06

Llama 4 Maverick

$0.15

Output Price per Million Tokens

Gemma 4 26B A4B

$0.33

Llama 4 Maverick

$0.60

Want to test both models live?

Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

Gemma 4 26B A4B Quirks & Gotchas

No developer gotchas reported.

Llama 4 Maverick Quirks & Gotchas

No developer gotchas reported.