Llama 4 (Meta) logo
B
7.9/10

Llama 4 (Meta)

VS
GLM / Z.ai (Zhipu AI) logoOur pick
A
8.0/10

GLM / Z.ai (Zhipu AI)

Llama 4 (Meta) vs GLM / Z.ai (Zhipu AI)

Tier-list head-to-head. GLM / Z.ai (Zhipu AI) takes the A-tier slot — here's the breakdown.

Last reviewed April 17, 2026· sweep-fresh

Spec sheet

At a glance

 Llama 4 (Meta) logoLlama 4 (Meta)GLM / Z.ai (Zhipu AI) logoGLM / Z.ai (Zhipu AI)
TierB-tierA-tierwin
Overall score7.9 / 108.0 / 10win
Free tierYesYes
Starting price$0$0
Best forDevelopers and teams who need a permissively-licensed open-weights model with strong tooling, long context …Teams that need genuine MIT-licensed frontier open weights with no commercial strings.
Last reviewed2026-04-132026-04-17

Head-to-head

Score showdown

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

Ease of use+1.5 GLM / Z.ai (Zhipu AI)
Llama 4 (Meta)
5.0
GLM / Z.ai (Zhipu AI)
6.5
Output qualityTie
Llama 4 (Meta)
8.5
GLM / Z.ai (Zhipu AI)
8.5
ValueTie
Llama 4 (Meta)
9.0
GLM / Z.ai (Zhipu AI)
9.0
Features+1.0 Llama 4 (Meta)
Llama 4 (Meta)
9.0
GLM / Z.ai (Zhipu AI)
8.0
Overall+0.1 GLM / Z.ai (Zhipu AI)
Llama 4 (Meta)
7.9
GLM / Z.ai (Zhipu AI)
8.0

Vibe check

Personality & tone

How each tool actually sounds when you talk to it.

Llama 4 (Meta)

The open-weight workhorse

Tone
Plain, helpful, and neutral. Meta's instruction-tuned Llama 4 reads like a sanitized ChatGPT -- useful for general tasks but without a strong persona of its own.
Quirks
The 'real' personality depends on the checkpoint you run. Base Llama 4 is bland by design; the interesting behaviors come from community fine-tunes (Nous, Hermes, Dolphin, etc.) that give it different voices and refusal patterns.
GLM / Z.ai (Zhipu AI)

The Z.ai research model

Tone
Academic and structured. GLM-4.6's instruction-tuned chat tends toward outlined, bullet-heavy responses and leans on established phrasing rather than casual voice.
Quirks
Strong on multilingual and tool use, weaker at playful conversation. Smaller community fine-tuning ecosystem than Llama or Qwen, so fewer 'flavored' checkpoints to pick from -- most deployments run the base instruction-tune.

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
GLM / Z.ai (Zhipu AI) logo

GLM / Z.ai (Zhipu AI)

Free tier available

  • Self-hosted (Free)$0
  • API (Z.ai / OpenRouter, GLM-5.1)$0.60/per 1M input tokens

Benchmark Head-to-Head

Llama 4 Maverick (17B/400B MoE) vs GLM-5.1 (744B MoE / 40B active)

BenchmarkLlama 4 (Meta)GLM / Z.ai (Zhipu AI)
MMLU-Pro80.5%81.2%
GPQA Diamond69.8%74.5%
HumanEval88%89.1%

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
  • More feature surface area for power users who'll use the depth
  • 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
GLM / Z.ai (Zhipu AI) logo

Pick GLM / Z.ai (Zhipu AI)if…

A
8.0/10
  • Easier to learn and use day-to-day -- friendlier onboarding curve
  • Teams that need genuine MIT-licensed frontier open weights with no commercial strings.
  • Especially strong for agentic workflows and vision (GLM-4.
  • Stronger on graduate-level science questions (+4.7% on GPQA Diamond)

Teams that need genuine MIT-licensed frontier open weights with no commercial strings. Especially strong for agentic workflows and vision (GLM-4.6V).

Visit GLM / Z.ai (Zhipu AI)

Bottom line

The verdict

Llama 4 (Meta) (A-tier, 7.9/10) and GLM / Z.ai (Zhipu AI) (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.

Pricing-wise, both tools have a free tier (Llama 4 (Meta) starts $0, GLM / Z.ai (Zhipu AI) starts $0), so you can test either without committing. Compare what each free tier actually unlocks -- usage caps, model access, and feature gates differ a lot more than the headline price suggests, especially as both vendors have tightened limits in 2026.

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 GLM / Z.ai (Zhipu AI) when teams that need genuine mit-licensed frontier open weights with no commercial strings. The two tools aren't fighting for the same person -- they're aiming at adjacent jobs that occasionally overlap. If you're squarely in GLM / Z.ai (Zhipu AI)'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 April 17, 2026Tier rubric · ease of use, output, value, features

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Built from our daily AI-tool sweep, last touched April 17, 2026. Honest tier-list reviews — no affiliate-link pieces disguised as advice. See the rubric or how we review.