FitMyLLM
NVIDIA· ADA LOVELACE

NVIDIA L4 24GB

Running LLMs on the L4 24GB — the long read: which models fit at which quantisation, and the settings worth changing. · Or what else $2,500 buys

VRAM
24 GB
HIGH-END
BANDWIDTH
300
GB/S
MODELS Q4
293/449
65%
7B Q4 SPEED
~34
FAST
▸ MODEL COVERAGE @ Q465% OF ALL
▸ ESTIMATED SPEED· BY MODEL SIZE @ Q4

Average speeds at Q4 quantization. Actual performance varies by model architecture and context length.

3B
~80
TOK/S
7B
~34
TOK/S
14B
~17
TOK/S
32B
~8
TOK/S
70B
39.4GB NEEDED
▸ MEASURED RIG REPORTS

We rent the machine and time every model on it: decode, VRAM peak, concurrency, watts and cost per million tokens. Yours may already be one of them — and two are free to read in full.

SEE THE REPORTS
▸ SPECIFICATIONS
VRAM
24 GB
BANDWIDTH
300 GB/s
FP16 COMPUTE
121 TFLOPS
TDP
72W
MEMORY
GDDR6
ARCHITECTURE
Ada Lovelace
CUDA CORES
7,680
TENSOR CORES
240
PCIE
Gen 4 x16
MSRP
$2,500
204
FAST MODELS · >30 TOK/S
Real-time chat speed
283
USABLE · >10 TOK/S
Comfortable for all tasks
293
TOTAL COMPATIBLE
Fit in VRAM at Q4
▸ RENT IT IN THE CLOUD

Buying L4 24GB costs $15–$40k and isn’t practical for most teams. Spin one up by the hour instead:

Spin up in ~60s. Pay by the second. Cancel anytime.

Some links are affiliate links — we may earn a small commission at no extra cost to you. This helps keep FitMyLLM free and independent.

▸ COMPATIBLE MODELS· 293
S
Falcon-H1R Tiny 90M0.09B
FALCON·256K CTX· CHAT· REASONING
2667
TOK/S · 2% VRAM
S
SmolLM2 135M0.135B
SMOLLM·2K CTX· CHAT
1778
TOK/S · 2% VRAM
S
nomic-embed-text-v1.5 100M0.14B
EMBEDDING·8K CTX· CHAT
1714
TOK/S · 2% VRAM
S
GPT-2 124M0.14B
GPT2·1K CTX· CHAT
1714
TOK/S · 2% VRAM
S
SmolVLM 256M0.256B
SMOLLM·8K CTX· CHAT· VISION
937
TOK/S · 3% VRAM
S
Gemma 3 270M0.27B
GEMMA·32K CTX· CHAT
889
TOK/S · 3% VRAM
S
Snowflake Arctic Embed M v2.00.305B
EMBEDDING·8K CTX· EMBEDDING· MULTILINGUAL
787
TOK/S · 3% VRAM
S
bge-large-en-v1.5 335M0.335B
EMBEDDING·1K CTX· CHAT
716
TOK/S · 3% VRAM
S
mxbai-embed-large-v10.335B
EMBEDDING·1K CTX· EMBEDDING
716
TOK/S · 3% VRAM
S
Snowflake Arctic Embed L0.335B
EMBEDDING·1K CTX· EMBEDDING
716
TOK/S · 3% VRAM
S
LFM2 350M0.35B
LFM·125K CTX· CHAT· TOOL_USE
686
TOK/S · 3% VRAM
S
SmolLM2 360M0.36B
SMOLLM·8K CTX· CHAT
667
TOK/S · 3% VRAM
S
GPT-2 Medium 345M0.38B
GPT2·1K CTX· CHAT
632
TOK/S · 3% VRAM
S
Qwen 2.5 0.5B0.5B
QWEN·32K CTX· CHAT
480
TOK/S · 3% VRAM
S
SmolVLM 500M0.5B
SMOLLM·8K CTX· CHAT· VISION
480
TOK/S · 3% VRAM
S
Falcon-H1 0.5B0.52B
FALCON·128K CTX· CHAT
462
TOK/S · 3% VRAM
S
BGE-M30.568B
EMBEDDING·8K CTX· EMBEDDING
423
TOK/S · 3% VRAM
S
Snowflake Arctic Embed L v2.00.568B
EMBEDDING·8K CTX· EMBEDDING· MULTILINGUAL
423
TOK/S · 3% VRAM
S
Qwen3-Embedding 0.6B0.6B
EMBEDDING·32K CTX· EMBEDDING· MULTILINGUAL
400
TOK/S · 4% VRAM
S
Falcon-H1R Tiny 0.6B0.6B
FALCON·32K CTX· CHAT· REASONING
400
TOK/S · 4% VRAM
S
Falcon Perception 0.6B0.6B
FALCON·4K CTX· VISION
400
TOK/S · 4% VRAM
S
Qwen 1.5 0.5B0.62B
QWEN·32K CTX· CHAT
387
TOK/S · 4% VRAM
S
LFM2 700M0.74B
LFM·125K CTX· CHAT· TOOL_USE
324
TOK/S · 4% VRAM
S
Qwen3 0.6B0.75B
QWEN·32K CTX· CHAT· REASONING
320
TOK/S · 4% VRAM
S
GPT-2 Large 774M0.81B
GPT2·1K CTX· CHAT
296
TOK/S · 4% VRAM
S
Qwen 3.5 0.8B0.87B
QWEN·256K CTX· CHAT· CODING· MULTILINGUAL
276
TOK/S · 4% VRAM
S
InternVL3 1B0.94B
OTHER·32K CTX· CHAT· VISION
255
TOK/S · 4% VRAM
S
MiniCPM5 1B1.08B
MINICPM·128K CTX· CHAT· REASONING· MULTILINGUAL
222
TOK/S · 5% VRAM
S
TinyLlama 1.1B1.1B
LLAMA·2K CTX· CHAT
218
TOK/S · 5% VRAM
S
LFM2.5-1.2B-Thinking1.2B
LFM·122K CTX· CHAT· REASONING· TOOL_USE
200
TOK/S · 5% VRAM
S
Llama-3.2-1B1.2B
LLAMA·4K CTX· CHAT
200
TOK/S · 5% VRAM
S
LFM2 1.2B1.2B
LFM·125K CTX· CHAT· TOOL_USE· MULTILINGUAL
200
TOK/S · 5% VRAM
S
Zamba2 1.2B1.2B
OTHER·4K CTX· CHAT
200
TOK/S · 5% VRAM
S
EXAONE-4.0-1.2B1.3B
EXAONE·64K CTX· CHAT
185
TOK/S · 5% VRAM
S
OPT 1.3B1.3B
OPT·2K CTX· CHAT
185
TOK/S · 5% VRAM
S
MiniCPM-V 4.61.3B
OTHER·256K CTX· CHAT· VISION
185
TOK/S · 5% VRAM
S
DeepSeek Coder 1.3B1.35B
DEEPSEEK·16K CTX· CODING
178
TOK/S · 5% VRAM
S
Phi-1 1.3B1.42B
PHI·2K CTX· CODING
169
TOK/S · 6% VRAM
S
Phi-1.5 1.3B1.42B
PHI·2K CTX· CHAT· CODING
169
TOK/S · 6% VRAM
S
LFM2 8B A1B8.3BMoE
LFM·125K CTX· CHAT· TOOL_USE· MULTILINGUAL
160
TOK/S · 23% VRAM
▸ NEXT STEP

Get personalized recommendations.

See ranked models with benchmark scores, run commands, and precise speed estimates for your L4 24GB.

WHAT THIS CARD IS WORTH

L4 24GB holds 293 of the models in our catalogue and is, in practice, a IQ4_XS card — the largest it takes is DeepSeek Coder 33B at IQ4_XS.

TOKENS/SEC PER $100
1.4
8B at Q4_K_M, so cards compare like for like
VRAM PER $100
0.96 GB
what memory costs on this card
THE BIGGEST IT TAKES
DeepSeek Coder 33B33B · IQ4_XS21.6 GB9 tok/sEST
DeepSeek-R1-Distill-Qwen-32B32.8B · IQ4_XS21.5 GB9 tok/sEST
Qwen3 32B32.8B · IQ4_XS21.5 GB9 tok/sEST
Qwen2.5-32B32.5B · IQ4_XS21.3 GB9 tok/sEST
Qwen 2.5 Coder 32B32.5B · IQ4_XS21.3 GB9 tok/sEST
QwQ-32B32.5B · IQ4_XS21.3 GB9 tok/sEST
Granite Switch 4.1 30B Preview32.24B · IQ4_XS21.1 GB9 tok/sEST
OLMo-2-0325-32B32.2B · IQ4_XS21.1 GB9 tok/sEST
AGAINST CARDS OF SIMILAR MEMORY
M3 Max (36GB)27 GB$2,4991.5 tok/s per $100
M3 Pro (36GB)27 GB$1,9991.2 tok/s per $100
RTX 509032 GB$1,9997.9 tok/s per $100
RTX 5090 D32 GB$1,9997.9 tok/s per $100
L4 24GB24 GB$2,5001.4 tok/s per $100

Neighbours in memory rather than in price: memory decides whether a card can do the job at all, so two cards of the same size at different prices is the comparison you are making. Ordered by memory, then bandwidth — not by the value column, which is worked out from bandwidth and price alone and therefore rewards a cheap card whatever its software stack does to that bandwidth in practice. Read it as one input, not as a ranking.

▸ DEVICE UNDER TEST

NVIDIA L4 24GB — 24 GB VRAM.

L4 24GB SPEC
BRAND
NVIDIA
VRAM
24 GB GDDR6
BANDWIDTH
300 GB/s
FP16 COMPUTE
121 TFLOPS
FP32 COMPUTE
30.3 TFLOPS
CUDA CORES
7,680
TENSOR CORES
240
TDP
72 W
ARCHITECTURE
Ada Lovelace
MSRP
$2500
▸ AI CAPABILITY
293/ 449 models @ Q4

With 24 GB VRAM and 300 GB/s bandwidth, this GPU handles models up to 30.5B parameters.

Speed ≈ bandwidth / model_size × efficiency. A 7B model at Q4 runs at ~34 tok/s.

RENT IT — LIVE PRICES
Checking what the clouds are charging…
§ 01TOP MODELS FOR L4 24GB
293 FIT · SHOWING 20
MODELSIZEVRAM Q4TOK/SAVG
Qwen3 30B A3B30.5B19.1 GB8046.7
Qwen3-Coder 30B-A3B30.5B19.1 GB7336.9
Qwen3-30B-A3B Instruct 250730.5B19.1 GB7343.0
MPT-30B30B18.8 GB826.8
OPT 30B30B18.8 GB86.3
Qwen3-Omni 30B-A3B30B18.8 GB8040.6
Granite 4.1 30B30B18.8 GB824.7
TranslateGemma 27B28.84B18.1 GB838.6
PaliGemma 2 28B28B17.6 GB938.6
ERNIE 4.5 VL 28B A3B Thinking28B17.6 GB80
Qwen3.5-27B27.8B17.5 GB959.4
Qwen 3.8 27B27.78B17.5 GB964.6
gemma-3-27b27.4B17.2 GB927.2
gemma-2-27b27.2B17.1 GB934.6
Qwen 3.6 27B27B17.0 GB941.1
Gemma 4 26B A4B26B16.4 GB6047.9
Aria 25B A3.9B25.3B16.0 GB6264.8
Mistral-Small-24B24B15.2 GB1025.0
Mistral-Small-3.1-24B24B15.2 GB1028.8
Magistral Small 24B24B15.2 GB1047.0