Qwen 2.5 72B
Alibaba · dense · 72.7B parameters · 131,072 context
Parameters
72.7B
Context Window
128K tokens
Architecture
Dense
Best GPU
H200 SXM
Cheapest API
$0.00/M
Quality Score
77/100
Intelligence Brief
Qwen 2.5 72B is a 72.7B parameter DENSE model from Alibaba, featuring Grouped Query Attention (GQA) with 80 layers and 8,192 hidden dimensions. With a 131,072 token context window, it supports tools, structured output, code, math, multilingual. On standardized benchmarks, it achieves MMLU 85.3, HumanEval 56, GSM8K 91.6. The most cost-effective API deployment is via featherless at $0.00/M output tokens. For self-hosted inference, H200 SXM delivers optimal throughput at $2553/month.
Provider pricing
6 providers · canonical: together| Provider | Input $/M | Output $/M ▲ | Notes |
|---|---|---|---|
| featherless | free | free | cheapest input · cheapest output |
| novita | $0.380 | $0.400 | — |
| openrouter | $0.360 | $0.400 | — |
| deepinfra | $0.350 | $0.400 | — |
| fireworks | $0.900 | $0.900 | — |
| togethercanonical | $1.20 | $1.20 | — |
Prices update via the nightly pricing cron + admin approvals at /admin/ingest-queue. The leaderboard's Input/Output cells show the canonical rate above; this table shows the full spread.
Recent changes
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Picks: same family first, then same vendor within ±2× params, then top tag-overlap matches. Price shown is the cheapest Output $/M across providers — the row's page shows the canonical anchor.
Architecture Details
Memory Requirements
BF16 Weights
145.4 GB
FP8 Weights
72.7 GB
INT4 Weights
36.4 GB
GPU Compatibility Matrix
Qwen 2.5 72B is compatible with 37% of GPU configurations across 41 GPUs at 3 precision levels.
GPU Recommendations
FP8 · 1 GPU · tensorrt-llm
100/100
score
Throughput
552.3 tok/s
Latency (ITL)
1.8ms
Est. TTFT
0ms
Cost/Month
$2553
Cost/M Tokens
$1.76
FP8 · 1 GPU · tensorrt-llm
98/100
score
Throughput
560.0 tok/s
Latency (ITL)
1.8ms
Est. TTFT
0ms
Cost/Month
$4261
Cost/M Tokens
$2.90
FP8 · 1 GPU · tensorrt-llm
98/100
score
Throughput
560.0 tok/s
Latency (ITL)
1.8ms
Est. TTFT
0ms
Cost/Month
$4271
Cost/M Tokens
$2.90
Deployment Options
API Deployment
featherless
$0.00/M
output tokens
Single GPU
H200 SXM
$2553/mo
Min VRAM: 73 GB
Multi-GPU
H100 SXM x2
560.0 tok/s
TP· $3587/mo
API Pricing Comparison
| Provider | Input $/M | Output $/M | Badges |
|---|---|---|---|
| featherless | $0.00 | $0.00 | Cheapest |
| novita | $0.38 | $0.40 | |
| openrouter | $0.36 | $0.40 | |
| deepinfra | $0.35 | $0.40 | |
| fireworks | $0.90 | $0.90 | |
| together | $1.20 | $1.20 |
Cost Analysis
| Provider | Input $/M | Output $/M | ~Monthly Cost |
|---|---|---|---|
| featherlessBest Value | $0.00 | $0.00 | $0 |
| novita | $0.38 | $0.40 | $4 |
| openrouter | $0.36 | $0.40 | $4 |
| deepinfra | $0.35 | $0.40 | $4 |
| fireworks | $0.90 | $0.90 | $9 |
| together | $1.20 | $1.20 | $12 |
Cost per 1,000 Requests
Short (500 tok)
$0.00
via featherless
Medium (2K tok)
$0.00
via featherless
Long (8K tok)
$0.00
via featherless
Performance Estimates
Throughput by GPU
VRAM Breakdown (H200 SXM, FP8)
Precision Impact
bf16
145.4 GB
weights/GPU
fp8
72.7 GB
weights/GPU
~552.3 tok/s
int4
36.4 GB
weights/GPU
Quality Benchmarks
Capabilities
Features
Supported Frameworks
Supported Precisions
Where to Deploy Qwen 2.5 72B
Self-Hosted Infrastructure
Similar Models
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Qwen 2.5 Math 72B
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Quality: 50
from $0.90/M
Qwen 2.5 VL 72B
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Molmo 72B
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Frequently Asked Questions
How much VRAM does Qwen 2.5 72B need for inference?
Qwen 2.5 72B requires approximately 145.4 GB of VRAM at BF16 precision, 72.7 GB at FP8, or 36.4 GB at INT4 quantization. Additional VRAM is needed for KV-cache (327680 bytes per token) and activations (~2.50 GB).
What is the best GPU for Qwen 2.5 72B?
The top recommended GPU for Qwen 2.5 72B is the H200 SXM using FP8 precision. It achieves approximately 552.3 tokens/sec at an estimated cost of $2553/month ($1.76/M tokens). Score: 100/100.
How much does Qwen 2.5 72B inference cost?
Qwen 2.5 72B API inference starts from $0.00/M input tokens and $0.00/M output tokens. Self-hosted inference costs depend on your GPU configuration — use our ROI calculator for a detailed breakdown.