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Llama Review 2026: Pricing, Benchmarks & Alternatives

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Meta

Meta's open-source powerhouse making frontier AI available to everyone

Category

chatbots

Starting At

Open Source

API

Available

Updated

2026-08-19

ResearchersSelf-hosted enterprise AIFine-tuning workflows

Model Variants

29 variants · Select to compare specs

Capability Fingerprint

Llama 4 Maverick

Speed

fast

Intelligence

low

Context

128k

Pricing

$0.42 / 1M tokens

Llama 4 Maverick by Meta. Optimized for efficiency.

Benchmarks

11 metrics
Swe Bench Verified
16.3%
Math
19.3%
Gpqa Diamond
67.1%
Mmlu Pro
80.9%
Hle
4.9%
Arc A G I2
17.8%
Aime2025
19.3%
Live Code Bench
39.7%
Mmlu
8.5%
Terminal Bench
6.8%
Speed
84.5%

Our Verdict

The open ecosystem's center of gravity — 8B to 405B, unmatched community.

Llama 4's span from 8B to 405B — with the flagship rivaling closed frontier models on reasoning and an 80.2% SWE-Bench Verified score — plus the largest fine-tuning and tooling community in open weights, keeps it the default starting point for self-hosted AI. The 405B model demands serious hardware, and Meta's app ecosystem is geo-restricted. If you are building on open models, you start here.

Who should use Llama: This tool excels for Researchers, Self-hosted enterprise AI, Fine-tuning workflows. Being open-source means no vendor lock-in and full control over your data. The The most capable fully open-weights model available pricing positions itcompetitively in the market.

Benchmark Analysis

Based on 11+ independent benchmarks, here's how Llama performs:

SWE-Bench
16.3%
Real-world coding tasks
ARC-AGI-2
17.8%
Abstract reasoning
GPQA Diamond
67.1%
Expert-level QA

Note: Benchmarks are verified against official vendor claims and independent testing. Scores last updated 2026-08-19. See our methodology for details.

Company Overview

Meta was founded in 2023 and is based in Menlo Park, CA.Llama is released under an open-source license, which means anyone can inspect the code, modify it, or deploy it privately without licensing fees.

Should you use Llama?

Use it if:
  • Researchers
  • Self-hosted enterprise AI
  • Fine-tuning workflows
Avoid if:
  • Requires heavy compute for 405B
  • Meta AI app is geo-restricted

Key Advantages

  • Fully open weights
  • Huge community support
  • Multiple sizes (8B to 405B)
  • Extensive fine-tuning ecosystem

Known Constraints

  • Requires heavy compute for 405B
  • Meta AI app is geo-restricted

Head-to-Head Comparisons

See how Llama stacks up against its closest competitors with detailed benchmark analysis, pricing breakdowns, and expert verdicts.

Benchmark Comparison

Real performance data from independent testing

Metric
LlamaThis
Gemini
Claude
ChatGPT
SiteSiteSiteSite
SWE-Bench (Coding)
80.2%
80.6%
87.6%
80.1%
Terminal Success (Agents)
62.4%
68.5%
69.4%
75.1%
Unit Logic (HumanEval)
91.2%
94.1%
94.5%
92.4%
GPQA Diamond (Science)
85.4%
94.3%
94.2%
94.4%
MATH (Reasoning)
96.5%
96.2%
95.8%
93.8%
MMLU (Knowledge)
88.4%
92.6%
91.5%
88.2%
Code Arena (ELO)
1861
1650
1678
Chat Arena (ELO)
1455
1583
1457
Context
128K tokens
1M tokens
200K tokens
400K tokens
Price
Open SourceFreemiumFreemiumFreemium
Best For
CodingReasoningValue
CodingReasoningAgenticValue
CodingReasoningAgentic
CodingReasoningAgentic
Llama:The most capable fully open-weights model available
Gemini:#1 on ARC-AGI-2 (77.1%)
Claude:#1 on SWE-Bench Verified (87.6%)
ChatGPT:Best for agentic tasks (75.1% Terminal-Bench)
Data from March 2026 independent benchmarksFull comparison

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