Llama 4 (Meta)
Our pickGemma 4 (Google)
Tier-list head-to-head. Gemma 4 (Google) takes the A-tier slot — here's the breakdown.
Spec sheet
| Llama 4 (Meta) | Gemma 4 (Google) | |
|---|---|---|
| Tier | B-tier | A-tierwin |
| Overall score | 7.9 / 10 | 8.3 / 10win |
| Free tier | Yes | Yes |
| Starting price | $0 | $0 |
| Best for | Developers and teams who need a permissively-licensed open-weights model with strong tooling, long context … | Developers and businesses who need a permissively licensed multimodal LLM they can self-host or fine-tune. |
| Last reviewed | 2026-04-13 | 2026-04-19 |
Head-to-head
Rated 1-10 on the same rubric across all 130 tools we cover.
Vibe check
How each tool actually sounds when you talk to it.
“The open-weight workhorse”
“The compact Google cousin”
What you'll pay
Look past the headline number -- entry-tier limits drive most cost surprises.
Free tier available
Free tier available
Llama 4 Maverick (17B/400B MoE) vs Gemma 4 31B
| Benchmark | Llama 4 (Meta) | Gemma 4 (Google) |
|---|---|---|
| GPQA Diamond | 69.8% | 84.3% |
| HumanEval | 88% | 85% |
The decision
Use-case anchors and category strengths, side by side.
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)Developers and businesses who need a permissively licensed multimodal LLM they can self-host or fine-tune. Especially good for multilingual use cases and on-device deployment.
Visit Gemma 4 (Google)Bottom line
Gemma 4 (Google) edges out Llama 4 (Meta) by 0.4 points (8.3 vs 7.9) -- a A-tier vs B-tier split that's narrow but real. Not a blowout; both belong on a shortlist. The score gap shows up most clearly in the categories that matter for Gemma 4 (Google)'s strengths, so if those categories are your priority, the lead translates.
Pricing-wise, both tools have a free tier (Llama 4 (Meta) starts $0, Gemma 4 (Google) 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 Gemma 4 (Google) when developers and businesses who need a permissively licensed multimodal llm they can self-host or fine-tune. The two tools aren't fighting for the same person -- they're aiming at adjacent jobs that occasionally overlap. If you're squarely in Gemma 4 (Google)'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: Gemma 4 (Google) is the safer default for most readers, but Llama 4 (Meta) is competitive enough that the tie-breaker is your specific workload, not the spec sheet.
Keep digging
Full Llama 4 (Meta) review
Tier B · 7.9/10
Full Gemma 4 (Google) review
Tier A · 8.3/10
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Gemma 4 (Google) alternatives
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Built from our daily AI-tool sweep, last touched April 19, 2026. Honest tier-list reviews — no affiliate-link pieces disguised as advice. See the rubric or how we review.