Coding AILlamaMIT

Phind-CodeLlama 34B

Phind/Phind-CodeLlama-34B-v2

Parameters

34B

Context

16K

Downloads

500

Likes

834

Architecture

transformer

View on HuggingFace

GPU Requirements

VRAM / RAM / disk estimates by quantization and usage scenario

QuantizationMinimumRecommendedProduction
FP1616bit
85.1 GB
RAM 127.6 · Disk 137.8
104.5 GB
RAM 156.7 · Disk 163.8
205.0 GB
RAM 307.5 · Disk 202.8
FP88bit
45.0 GB
RAM 67.5 · Disk 88.4
62.6 GB
RAM 93.9 · Disk 114.4
161.3 GB
RAM 242.0 · Disk 153.4
INT88bit
45.0 GB
RAM 67.5 · Disk 88.4
62.6 GB
RAM 93.9 · Disk 114.4
161.3 GB
RAM 242.0 · Disk 153.4
AWQ4bit
25.7 GB
RAM 38.6 · Disk 64.6
42.4 GB
RAM 63.6 · Disk 90.6
140.3 GB
RAM 210.4 · Disk 129.6
GPTQ4bit
26.0 GB
RAM 39.0 · Disk 64.9
42.7 GB
RAM 64.0 · Disk 90.9
140.5 GB
RAM 210.8 · Disk 129.9
GGUF4bit
26.5 GB
RAM 39.7 · Disk 65.6
43.2 GB
RAM 64.8 · Disk 91.6
141.1 GB
RAM 211.6 · Disk 130.6

GPU Recommendations

Best ValueBEST

1× H100 SXM

80 GB VRAM

$1,170/mo

≈ 203.9 tok/s

Effective production throughput ≈ 142.7 tok/s

score 0.631

Deploy on vast ↗
Cheapest

4× Tesla V100

64 GB VRAM

$81.2/mo

≈ 0 tok/s (N/A — benchmark unavailable)

Effective production throughput ≈ 0 tok/s

score 0.5751

Deploy on vast ↗
Performance

8× H200 SXM

1128 GB VRAM

$20,440/mo

≈ 934.9 tok/s

Effective production throughput ≈ 654.4 tok/s

score 0.2197

Min Complexity

1× RTX A6000

48 GB VRAM

$210/mo

≈ 46.7 tok/s

Effective production throughput ≈ 32.7 tok/s

score 0.6554

Deploy on vast ↗

💬 Community — real deployment experience

0 Articles · 0 Benchmarks

View Community →

GPUs that fit (single card)

RTX A6000

48 GB VRAM

$210

/mo · vast

L40S

48 GB VRAM

$341

/mo · vast

RTX PRO 6000 WS

48 GB VRAM

$482

/mo · vast

RTX PRO 6000 S

48 GB VRAM

$633

/mo · vast

A100 80GB

80 GB VRAM

$876

/mo · vast

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