Llama 4 (Meta) logo
B
7.9/10

Llama 4 (Meta)

VS
Augment Code Intent logoOur pick
A
8.0/10

Augment Code Intent

Llama 4 (Meta) vs Augment Code Intent

Tier-list head-to-head. Augment Code Intent takes the A-tier slot — here's the breakdown.

Last reviewed June 9, 2026· sweep-fresh

Spec sheet

At a glance

 Llama 4 (Meta) logoLlama 4 (Meta)Augment Code Intent logoAugment Code Intent
TierB-tierA-tierwin
Overall score7.9 / 108.0 / 10win
Free tierYeswinNo
Starting price$0Included in Auggie subscription
Best forDevelopers and teams who need a permissively-licensed open-weights model with strong tooling, long context …Engineering teams already using Augment Code's Auggie or running mixed Claude-Code + Codex workflows who wa…
Last reviewed2026-06-092026-04-21

Head-to-head

Score showdown

Rated 1-10 on the same rubric across all 130 tools we cover.

Ease of use+2.0 Augment Code Intent
Llama 4 (Meta)
5.0
Augment Code Intent
7.0
Output quality+0.5 Llama 4 (Meta)
Llama 4 (Meta)
8.5
Augment Code Intent
8.0
Value+1.0 Llama 4 (Meta)
Llama 4 (Meta)
9.0
Augment Code Intent
8.0
FeaturesTie
Llama 4 (Meta)
9.0
Augment Code Intent
9.0
Overall+0.1 Augment Code Intent
Llama 4 (Meta)
7.9
Augment Code Intent
8.0

What you'll pay

Pricing snapshot

Look past the headline number -- entry-tier limits drive most cost surprises.

Llama 4 (Meta) logo

Llama 4 (Meta)

Free tier available

  • Self-hosted (Free)$0
  • Cloud API (Together.ai, Fireworks, Groq)$3-8/per 1M input tokens
Augment Code Intent logo

Augment Code Intent

No free tier

  • Auggie rate (Augment Code users)Included in Auggie subscription
  • Standalone (non-Augment users)TBD

Benchmark Head-to-Head

Llama 4 Maverick (17B/400B MoE) benchmarks — Augment Code Intent has no published benchmarks

BenchmarkScore
MMLU-Pro80.5%
GPQA Diamond69.8%
HumanEval88%
MMMU (multimodal)73.4%

The decision

Which should you pick?

Use-case anchors and category strengths, side by side.

Llama 4 (Meta) logo

Pick Llama 4 (Meta)if…

B
7.9/10
  • Better value at the price you'll actually pay (9.0/10 on value)
  • Free tier lets you actually try it before paying
  • Developers and teams who need a permissively-licensed open-weights model with strong tooling, long context (Scout), or multimodal (Maverick).
  • Safe default choice given the ecosystem.

Developers and teams who need a permissively-licensed open-weights model with strong tooling, long context (Scout), or multimodal (Maverick). Safe default choice given the ecosystem.

Visit Llama 4 (Meta)
Our pick
Augment Code Intent logo

Pick Augment Code Intentif…

A
8.0/10
  • Easier to learn and use day-to-day -- friendlier onboarding curve
  • Engineering teams already using Augment Code's Auggie or running mixed Claude-Code + Codex workflows who want higher-level orchestration than writing LangGraph graphs from scratch.
  • Also teams that want git-worktree-isolated parallel agent work with a verifier in the loop.

Engineering teams already using Augment Code's Auggie or running mixed Claude-Code + Codex workflows who want higher-level orchestration than writing LangGraph graphs from scratch. Also teams that want git-worktree-isolated parallel agent work with a verifier in the loop.

Visit Augment Code Intent

Bottom line

The verdict

Llama 4 (Meta) (A-tier, 7.9/10) and Augment Code Intent (B-tier, 8.0/10) are within margin-of-error of each other on overall score. There's no decisive winner -- the right pick comes down to how you'll actually use the tool, not which scored higher in the abstract. We rate them on the same rubric (ease of use, output quality, value, features), and on this pair the rubric is calling it a draw.

On pricing, Llama 4 (Meta) starts free while Augment Code Intent requires a paid plan from day one (Included in Auggie subscription+). If you're testing the waters or running an occasional workload, that gap matters more than the score differential. Llama 4 (Meta) starts at $0; Augment Code Intent starts at Included in Auggie subscription. Compare what each entry tier actually unlocks before you compare list prices -- the limits matter more than the headline number.

By use case: pick Llama 4 (Meta) when developers and teams who need a permissively-licensed open-weights model with strong tooling, long context (scout), or multimodal (maverick). Pick Augment Code Intent when engineering teams already using augment code's auggie or running mixed claude-code + codex workflows who want higher-level orchestration than writing langgraph graphs from scratch. The two tools aren't fighting for the same person -- they're aiming at adjacent jobs that occasionally overlap. If you're squarely in Augment Code Intent's lane, the tier-list ranking and the use-case fit point the same direction; if you're in Llama 4 (Meta)'s lane, the score gap matters less than the fit.

Bottom line: this pair is a coin flip on raw scores. Choose by use-case fit, free-tier availability, and which one you can actually try without committing. Re-evaluate in 60-90 days -- both vendors are shipping fast in 2026.

AIToolTier verdictLast reviewed June 9, 2026Tier rubric · ease of use, output, value, features

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Built from our daily AI-tool sweep, last touched June 9, 2026. Honest tier-list reviews — no affiliate-link pieces disguised as advice. See the rubric or how we review.