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Gemma 4 31B vs Llama 3.3 70B Instruct

Side-by-side VRAM requirements, benchmark scores, and GPU compatibility for local AI inference.

Quick verdict

Gemma 4 31B is more hardware-efficient — it needs 21.0 GB at Q4_K_M vs 42.2 GB for Llama 3.3 70B Instruct, fitting on 50 GPUs natively.

VRAM at each quantization (8k context)

QuantGemma 4 31BLlama 3.3 70B InstructDiff
FP1673.0 GB159.8 GB-54%
Q838.3 GB81.4 GB-53%
Q6_K29.6 GB61.8 GB-52%
Q5_K_M25.3 GB52.0 GB-51%
Q4_K_M21.0 GB42.2 GB-50%
Q3_K_M17.5 GB34.4 GB-49%
Q2_K14.0 GB26.5 GB-47%

Diff is Gemma 4 31B relative to Llama 3.3 70B Instruct. Green = lower VRAM (fits more GPUs).

Model specifications

SpecGemma 4 31BLlama 3.3 70B Instruct
OrgGoogleMeta
Parameters31B70B
ArchitectureDenseDense
Context250k tokens125k tokens
Modalitiestext, visiontext
LicenseApache 2.0Llama 3.3 Community
CommercialYesYes
Released2026-04-022024-12-06
GPUs (native)50 / 6738 / 67

GPUs that run only Gemma 4 31B(12)

GPUs that run only Llama 3.3 70B Instruct(0)

Every GPU that runs Llama 3.3 70B Instruct also runs Gemma 4 31B.

GPUs that run both natively(38)

Which should you use?

Choose Gemma 4 31B if:
  • • You have limited VRAM — it's a smaller model needing 21.0 GB vs 42.2 GB
  • • Long context matters — it supports 250k tokens vs 125k
  • • You need vision/image understanding
Choose Llama 3.3 70B Instruct if:
  • • You want maximum capability and have a 43 GB+ GPU

Frequently asked questions

Which is better, Gemma 4 31B or Llama 3.3 70B Instruct?
Gemma 4 31B has 31B parameters vs 70B for Llama 3.3 70B Instruct, so Llama 3.3 70B Instruct is the larger model. Gemma 4 31B is more hardware-efficient, needing 21.0 GB at Q4_K_M vs 42.2 GB. Gemma 4 31B runs on more GPUs natively (50 vs 38).
How much VRAM does Gemma 4 31B need vs Llama 3.3 70B Instruct?
At Q4_K_M quantization with 8k context, Gemma 4 31B needs approximately 21.0 GB of VRAM, while Llama 3.3 70B Instruct needs 42.2 GB. At FP16, Gemma 4 31B requires 73.0 GB vs 159.8 GB for Llama 3.3 70B Instruct.
Can you run Gemma 4 31B on the same GPUs as Llama 3.3 70B Instruct?
Yes, 38 GPUs can run both natively in VRAM, including NVIDIA RTX 5090, NVIDIA H100 80GB, NVIDIA A100 80GB. However, 12 GPUs can run Gemma 4 31B but not Llama 3.3 70B Instruct, and no GPU can run Llama 3.3 70B Instruct without also fitting Gemma 4 31B.
What is the difference between Gemma 4 31B and Llama 3.3 70B Instruct?
Gemma 4 31B has 31B parameters (dense) with a 250k context window. Llama 3.3 70B Instruct has 70B parameters (dense) with a 125k context window. Licensing differs: Gemma 4 31B is Apache 2.0 while Llama 3.3 70B Instruct is Llama 3.3 Community.
Which model fits in 24 GB of VRAM, Gemma 4 31B or Llama 3.3 70B Instruct?
Only Gemma 4 31B fits in 24 GB at Q4_K_M (21.0 GB). Llama 3.3 70B Instruct needs 42.2 GB, requiring a larger GPU.
Full Gemma 4 31B page →Full Llama 3.3 70B Instruct page →Check your hardware →