⚔ AI Comparison

7 Best Llama Alternatives in 2026 (We Tested Them All)

Llama 4 Maverick vs Top Alternatives Last tested April 2026
🏆 Overall Winner
Gemma 4 31B (Best Overall)
Llama 4 Maverick was groundbreaking when it launched, but the open-source LLM landscape has exploded past it. GLM-5 and Qwen 3.5 dominate reasoning benchmarks, Gemma 4 delivers frontier-level performance in a fraction of the size, and DeepSeek R1 remains the math/reasoning king. Unless you specifically need Maverick's 10M context window, there are now stronger options at every price point and hardware tier.

Performance Scores

Llama 4 Maverick
7.0
Top Alternatives
9.0

Strengths & Weaknesses

Llama 4 Maverick
  • Massive 10M token context window — largest among open models
  • 400B total parameters with efficient MoE (17B active per token)
  • Strong multilingual and multimodal capabilities
  • Extremely cheap API access at $0.15-0.20/1M input tokens
  • Backed by Meta with large community and ecosystem support
  • Coding performance disappoints at 43.4% on LiveCodeBench v6 — 17B active params spread too thin
  • Now trails GLM-5, Qwen 3.5, and Gemma 4 on most major benchmarks
  • Llama Community License is more restrictive than Apache 2.0
  • Requires significant hardware for self-hosting (400B total params)
  • BenchLM scores dropped to 18 — below even Llama 3.1 405B at 43
Top Alternatives
  • GLM-5.1 tops SWE-Bench Pro ahead of GPT-5.4 and Claude Opus 4.6
  • Gemma 4 31B achieves 80% LiveCodeBench v6 — nearly 2x Maverick's coding score
  • Qwen 3.5 offers 9 model sizes from 0.8B to 397B for every deployment scenario
  • DeepSeek R1 hits 97.3% on MATH-500 for pure reasoning tasks
  • Most alternatives ship under Apache 2.0 with zero usage restrictions
  • GLM-5 and DeepSeek face geopolitical and data sovereignty concerns for some enterprises
  • Qwen 3.5 397B still requires serious infrastructure for self-hosting
  • Gemma 4 has shorter context (256K vs Maverick's 10M)
  • DeepSeek V4 not yet publicly released — still waiting on official launch
  • Smaller models trade performance for efficiency — no free lunch

Which Should You Choose?

Choose Llama 4 Maverick if…
You need the absolute largest context window (10M tokens) for processing massive documents, codebases, or datasets in a single pass. You're already in the Meta/Llama ecosystem with existing fine-tunes and tooling. You need strong multilingual capabilities across 20+ languages. You want the cheapest frontier-class API pricing.
Choose Top Alternatives if…
You need strong coding performance — pick Gemma 4 (80% LiveCodeBench) or GLM-5.1 (tops SWE-Bench Pro). You want unrestricted commercial use — Gemma 4 ships under Apache 2.0 with zero restrictions. You need top reasoning — GLM-5 scores 85 on BenchLM, Qwen 3.5 scores 81. You want to run locally on modest hardware — Gemma 4 26B MoE activates only 3.8B params. You need math/science — DeepSeek R1 at 97.3% MATH-500 is untouchable.

Pricing

Llama 4 Maverick
Free weights (open-source). API via providers: ~$0.15-0.20/1M input, ~$0.60/1M output tokens. Self-hosting requires 8x A100 80GB or equivalent.
Top Alternatives
Gemma 4: Free (Apache 2.0), runs on single GPU. Qwen 3.5 Flash: $0.10/1M input. GLM-5: API pricing varies by provider. DeepSeek R1: ~$0.14/1M input, $0.55/1M output.

Sample Prompt Tests

Test 1 Tie wins

"Summarize a 50-page technical whitepaper"

Llama 4 Maverick

Maverick excels here — its 10M context window swallows entire documents without chunking. Produces well-structured summaries with key findings highlighted.

Top Alternatives

Gemma 4 (256K context) handles most documents fine. Qwen 3.5 (262K) similar. For truly massive documents, Maverick still wins.

Why Tie wins: Maverick's 10M context window is unmatched for ultra-long document processing

Test 2 Tie wins

"Debug a complex React component with state management issues"

Llama 4 Maverick

Maverick identifies the bug but suggests a verbose fix. Misses the more elegant useReducer pattern. 43.4% LiveCodeBench score shows.

Top Alternatives

Gemma 4 nails it — identifies the stale closure, suggests useReducer, and explains the mental model. 80% LiveCodeBench.

Why Tie wins: Gemma 4 scores nearly 2x on coding benchmarks despite being 13x smaller

Bottom Line

Our Verdict Llama 4 Maverick was a milestone for open-source AI, but in April 2026, it's no longer the default recommendation. Gemma 4 31B is the best all-around open model for most developers — it ranks #3 on LMArena, scores 85.2% MMLU Pro, runs on a single GPU, and ships under Apache 2.0. For pure reasoning, GLM-5 leads. For math, DeepSeek R1 is king. For maximum flexibility across model sizes, Qwen 3.5's nine-size lineup can't be beat. Maverick still earns its place if you need that 10M context window or are locked into the Llama ecosystem — but for new projects, start with Gemma 4 and only look elsewhere if it doesn't fit your specific use case.

Test these models yourself

Compare Llama 4 Maverick and Top Alternatives side-by-side with your own prompts — free.

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