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See what this model actually costs to serve.

Fit is always evaluated when model sizing is available. GPU rent, paid idle capacity, API crossover, and measured optimization appear only when their required evidence exists. When the API wins, the page says so.

Qwen2.5-7B-Instruct fits on 1 x NVIDIA RTX 6000 Ada 48 GB, but serving cost is withheld.

Fit is always evaluated when model sizing is available. GPU rent, paid idle capacity, API crossover, and measured optimization appear only when their required evidence exists. When the API wins, the page says so.

Model

Qwen/Qwen2.5-7B-Instruct

GPU

NVIDIA RTX 6000 Ada 48 GB

Requests/day

50,000

GPU count

1

Quantization

FP16

Tokens/request

500 in, 500 out

Charts appear only when evidence existsUtilization defaults to 30%

Configure the workload

Change the inputs, then calculate a shareable result.

Hugging Face model

Utilization assumption

Defaulted to 30% so the page does not manufacture a self-hosting win.

Derived utilization

Needs throughput

Idle share paid

Needs throughput

Utilization assumption30%

A steady production service with real peaks and troughs.

At this level about 70% of every rented GPU hour sits idle, and it is billed at the same rate as a busy one.

Estimated memory fit

Cost needs a throughput source.

The estimated fit verdict, compatible GPUs, and reproducing command are still useful. Money stays absent until this traffic shape has a complete measured, cited, or physics-bound evidence path.

Model

Qwen/Qwen2.5-7B-Instruct

Hardware

1 x NVIDIA RTX 6000 Ada 48 GB, FP16

Memory fit

Weights and KV cache stay separate so the fit is reproducible.

15.2 GB
Model weights
0.5 GB
KV cache
18.1 GB
Total required
43.2 GB
Available
8,192 tokens
Served context used
2.4 GB
Runtime overhead
Exact transformer shape
KV cache method

Decode bandwidth ceiling

A physics bound, not an expected throughput result.

63 output tok/sCeiling

Bandwidth decode CEILING, not expected throughput. Ideal tensor-parallel scaling is assumed. Real decode throughput is lower.

Decode ceiling derived from GPU memory bandwidth and model weight bytes, as of 2026-08-08

Provider price spread, NVIDIA RTX 6000 Ada 48 GB

Dated GPU-hour rental prices for this hardware. They are not monthly serving totals because throughput evidence is missing.

Scroll horizontally to read every chart label and value.

DigitalOcean, GPU Droplets: $1.57, on demand GPU-hour rate, captured 2026-08-08 (1 day ago). Cheapest: RunPod, Community Cloud: $0.74, on demand GPU-hour rate, captured 2026-08-08 (1 day ago). RunPod, Secure Cloud: $0.77, on demand GPU-hour rate, captured 2026-08-08 (1 day ago). Verda: $1.04, on demand GPU-hour rate, captured 2026-08-08 (1 day ago).

  • DigitalOcean, GPU Droplets$1.57
  • Cheapest: RunPod, Community Cloud$0.74
  • RunPod, Secure Cloud$0.77
  • Verda$1.04
Source:
  • DigitalOcean, GPU Droplets, on demand, 1 day ago, captured 2026-08-08
  • RunPod, Community Cloud, on demand, 1 day ago, captured 2026-08-08
  • RunPod, Secure Cloud, on demand, 1 day ago, captured 2026-08-08
  • Verda, on demand, 1 day ago, captured 2026-08-08
+What this chart means

These are GPU-hour rental prices only. A monthly serving total requires throughput evidence and remains absent.

Reproduce with vLLM

The exact command attached to this result.

vllm serve 'Qwen/Qwen2.5-7B-Instruct' --dtype float16 --tensor-parallel-size 1 --max-model-len 8192 --gpu-memory-utilization 0.9

Not measured on this config yet

No site-wide multiplier is applied. Run the exact configuration to create a receipt before comparing its measured baseline with RunInfra.

Run this configuration

Sources and caveats

Every published number keeps its source and date.

Provenance

  • Hugging Face model API revision sha

    As of 2026-08-08

  • Hugging Face model API safetensors.total

    As of 2026-08-08

  • config.json:max_position_embeddings

    As of 2026-08-08

  • config.json:architectures[0]

    As of 2026-08-08

  • NVIDIA RTX 6000 Ada Generation datasheet

    As of 2026-08-08

  • Hugging Face config.json transformer shape

    As of 2026-08-08

  • RunInfra Engine feasibility runtime-overhead policy

    As of 2026-08-09

  • Decode ceiling derived from GPU memory bandwidth and model weight bytes

    As of 2026-08-08

  • vLLM serve CLI documentation

    As of 2026-08-08

  • NVIDIA L4 product specification

    As of 2026-08-08

  • NVIDIA A10 datasheet

    As of 2026-08-08

  • NVIDIA L40S product specification

    As of 2026-08-08

  • NVIDIA A100 product specification

    As of 2026-08-08

Caveats

  • +Served context is 8192 tokens. It is a serving-capacity decision and is not inferred from average input or output tokens.
  • +KV cache uses the exact transformer-shape formula with 28 layers, 4 KV heads, and head dimension 128.
  • +Runtime overhead adds 2.36 GB to totalRequiredGb. This approximate 15% policy allowance covers CUDA context, activations, and vLLM overhead. Deployment-time profiling, including CUDA graph capture and allocator behavior, can differ.
  • +Bandwidth decode CEILING, not expected throughput. Ideal tensor-parallel scaling is assumed. Real decode throughput is lower.
  • +No dense compute ceiling is cited for fp16 on NVIDIA RTX 6000 Ada 48 GB. The available physics bound is decode-only, so the entry point returns no cost instead of copying decode throughput into the input field.
  • +CalcInput has no GPU provider selector. The calculation uses the lowest supplied on-demand rate for RTX-6000-Ada: RunPod, Community Cloud at $0.74/GPU-hour.

Estimated memory fit

Cost needs a throughput source.

The estimated fit verdict, compatible GPUs, and reproducing command are still useful. Money stays absent until this traffic shape has a complete measured, cited, or physics-bound evidence path.

Model

Qwen/Qwen2.5-7B-Instruct

Hardware

1 x NVIDIA RTX 6000 Ada 48 GB, FP16

Memory fit

Weights and KV cache stay separate so the fit is reproducible.

15.2 GB
Model weights
0.5 GB
KV cache
18.1 GB
Total required
43.2 GB
Available
8,192 tokens
Served context used
2.4 GB
Runtime overhead
Exact transformer shape
KV cache method

Decode bandwidth ceiling

A physics bound, not an expected throughput result.

63 output tok/sCeiling

Bandwidth decode CEILING, not expected throughput. Ideal tensor-parallel scaling is assumed. Real decode throughput is lower.

Decode ceiling derived from GPU memory bandwidth and model weight bytes, as of 2026-08-08

Provider price spread, NVIDIA RTX 6000 Ada 48 GB

Dated GPU-hour rental prices for this hardware. They are not monthly serving totals because throughput evidence is missing.

Scroll horizontally to read every chart label and value.

DigitalOcean, GPU Droplets: $1.57, on demand GPU-hour rate, captured 2026-08-08 (1 day ago). Cheapest: RunPod, Community Cloud: $0.74, on demand GPU-hour rate, captured 2026-08-08 (1 day ago). RunPod, Secure Cloud: $0.77, on demand GPU-hour rate, captured 2026-08-08 (1 day ago). Verda: $1.04, on demand GPU-hour rate, captured 2026-08-08 (1 day ago).

  • DigitalOcean, GPU Droplets$1.57
  • Cheapest: RunPod, Community Cloud$0.74
  • RunPod, Secure Cloud$0.77
  • Verda$1.04
Source:
  • DigitalOcean, GPU Droplets, on demand, 1 day ago, captured 2026-08-08
  • RunPod, Community Cloud, on demand, 1 day ago, captured 2026-08-08
  • RunPod, Secure Cloud, on demand, 1 day ago, captured 2026-08-08
  • Verda, on demand, 1 day ago, captured 2026-08-08
+What this chart means

These are GPU-hour rental prices only. A monthly serving total requires throughput evidence and remains absent.

Reproduce with vLLM

The exact command attached to this result.

vllm serve 'Qwen/Qwen2.5-7B-Instruct' --dtype float16 --tensor-parallel-size 1 --max-model-len 8192 --gpu-memory-utilization 0.9

Not measured on this config yet

No site-wide multiplier is applied. Run the exact configuration to create a receipt before comparing its measured baseline with RunInfra.

Run this configuration

Sources and caveats

Every published number keeps its source and date.

Provenance

  • Hugging Face model API revision sha

    As of 2026-08-08

  • Hugging Face model API safetensors.total

    As of 2026-08-08

  • config.json:max_position_embeddings

    As of 2026-08-08

  • config.json:architectures[0]

    As of 2026-08-08

  • NVIDIA RTX 6000 Ada Generation datasheet

    As of 2026-08-08

  • Hugging Face config.json transformer shape

    As of 2026-08-08

  • RunInfra Engine feasibility runtime-overhead policy

    As of 2026-08-09

  • Decode ceiling derived from GPU memory bandwidth and model weight bytes

    As of 2026-08-08

  • vLLM serve CLI documentation

    As of 2026-08-08

  • NVIDIA L4 product specification

    As of 2026-08-08

  • NVIDIA A10 datasheet

    As of 2026-08-08

  • NVIDIA L40S product specification

    As of 2026-08-08

  • NVIDIA A100 product specification

    As of 2026-08-08

Caveats

  • +Served context is 8192 tokens. It is a serving-capacity decision and is not inferred from average input or output tokens.
  • +KV cache uses the exact transformer-shape formula with 28 layers, 4 KV heads, and head dimension 128.
  • +Runtime overhead adds 2.36 GB to totalRequiredGb. This approximate 15% policy allowance covers CUDA context, activations, and vLLM overhead. Deployment-time profiling, including CUDA graph capture and allocator behavior, can differ.
  • +Bandwidth decode CEILING, not expected throughput. Ideal tensor-parallel scaling is assumed. Real decode throughput is lower.
  • +No dense compute ceiling is cited for fp16 on NVIDIA RTX 6000 Ada 48 GB. The available physics bound is decode-only, so the entry point returns no cost instead of copying decode throughput into the input field.
  • +CalcInput has no GPU provider selector. The calculation uses the lowest supplied on-demand rate for RTX-6000-Ada: RunPod, Community Cloud at $0.74/GPU-hour.

Estimated memory fit

Cost needs a throughput source.

The estimated fit verdict, compatible GPUs, and reproducing command are still useful. Money stays absent until this traffic shape has a complete measured, cited, or physics-bound evidence path.

Model

Qwen/Qwen2.5-7B-Instruct

Hardware

1 x NVIDIA RTX 6000 Ada 48 GB, FP16

Memory fit

Weights and KV cache stay separate so the fit is reproducible.

15.2 GB
Model weights
0.5 GB
KV cache
18.1 GB
Total required
43.2 GB
Available
8,192 tokens
Served context used
2.4 GB
Runtime overhead
Exact transformer shape
KV cache method

Decode bandwidth ceiling

A physics bound, not an expected throughput result.

63 output tok/sCeiling

Bandwidth decode CEILING, not expected throughput. Ideal tensor-parallel scaling is assumed. Real decode throughput is lower.

Decode ceiling derived from GPU memory bandwidth and model weight bytes, as of 2026-08-08

Provider price spread, NVIDIA RTX 6000 Ada 48 GB

Dated GPU-hour rental prices for this hardware. They are not monthly serving totals because throughput evidence is missing.

Scroll horizontally to read every chart label and value.

DigitalOcean, GPU Droplets: $1.57, on demand GPU-hour rate, captured 2026-08-08 (1 day ago). Cheapest: RunPod, Community Cloud: $0.74, on demand GPU-hour rate, captured 2026-08-08 (1 day ago). RunPod, Secure Cloud: $0.77, on demand GPU-hour rate, captured 2026-08-08 (1 day ago). Verda: $1.04, on demand GPU-hour rate, captured 2026-08-08 (1 day ago).

  • DigitalOcean, GPU Droplets$1.57
  • Cheapest: RunPod, Community Cloud$0.74
  • RunPod, Secure Cloud$0.77
  • Verda$1.04
Source:
  • DigitalOcean, GPU Droplets, on demand, 1 day ago, captured 2026-08-08
  • RunPod, Community Cloud, on demand, 1 day ago, captured 2026-08-08
  • RunPod, Secure Cloud, on demand, 1 day ago, captured 2026-08-08
  • Verda, on demand, 1 day ago, captured 2026-08-08
+What this chart means

These are GPU-hour rental prices only. A monthly serving total requires throughput evidence and remains absent.

Reproduce with vLLM

The exact command attached to this result.

vllm serve 'Qwen/Qwen2.5-7B-Instruct' --dtype float16 --tensor-parallel-size 1 --max-model-len 8192 --gpu-memory-utilization 0.9

Not measured on this config yet

No site-wide multiplier is applied. Run the exact configuration to create a receipt before comparing its measured baseline with RunInfra.

Run this configuration

Sources and caveats

Every published number keeps its source and date.

Provenance

  • Hugging Face model API revision sha

    As of 2026-08-08

  • Hugging Face model API safetensors.total

    As of 2026-08-08

  • config.json:max_position_embeddings

    As of 2026-08-08

  • config.json:architectures[0]

    As of 2026-08-08

  • NVIDIA RTX 6000 Ada Generation datasheet

    As of 2026-08-08

  • Hugging Face config.json transformer shape

    As of 2026-08-08

  • RunInfra Engine feasibility runtime-overhead policy

    As of 2026-08-09

  • Decode ceiling derived from GPU memory bandwidth and model weight bytes

    As of 2026-08-08

  • vLLM serve CLI documentation

    As of 2026-08-08

  • NVIDIA L4 product specification

    As of 2026-08-08

  • NVIDIA A10 datasheet

    As of 2026-08-08

  • NVIDIA L40S product specification

    As of 2026-08-08

  • NVIDIA A100 product specification

    As of 2026-08-08

Caveats

  • +Served context is 8192 tokens. It is a serving-capacity decision and is not inferred from average input or output tokens.
  • +KV cache uses the exact transformer-shape formula with 28 layers, 4 KV heads, and head dimension 128.
  • +Runtime overhead adds 2.36 GB to totalRequiredGb. This approximate 15% policy allowance covers CUDA context, activations, and vLLM overhead. Deployment-time profiling, including CUDA graph capture and allocator behavior, can differ.
  • +Bandwidth decode CEILING, not expected throughput. Ideal tensor-parallel scaling is assumed. Real decode throughput is lower.
  • +No dense compute ceiling is cited for fp16 on NVIDIA RTX 6000 Ada 48 GB. The available physics bound is decode-only, so the entry point returns no cost instead of copying decode throughput into the input field.
  • +CalcInput has no GPU provider selector. The calculation uses the lowest supplied on-demand rate for RTX-6000-Ada: RunPod, Community Cloud at $0.74/GPU-hour.

Estimated memory fit

Cost needs a throughput source.

The estimated fit verdict, compatible GPUs, and reproducing command are still useful. Money stays absent until this traffic shape has a complete measured, cited, or physics-bound evidence path.

Model

Qwen/Qwen2.5-7B-Instruct

Hardware

1 x NVIDIA RTX 6000 Ada 48 GB, FP16

Memory fit

Weights and KV cache stay separate so the fit is reproducible.

15.2 GB
Model weights
0.5 GB
KV cache
18.1 GB
Total required
43.2 GB
Available
8,192 tokens
Served context used
2.4 GB
Runtime overhead
Exact transformer shape
KV cache method

Decode bandwidth ceiling

A physics bound, not an expected throughput result.

63 output tok/sCeiling

Bandwidth decode CEILING, not expected throughput. Ideal tensor-parallel scaling is assumed. Real decode throughput is lower.

Decode ceiling derived from GPU memory bandwidth and model weight bytes, as of 2026-08-08

Provider price spread, NVIDIA RTX 6000 Ada 48 GB

Dated GPU-hour rental prices for this hardware. They are not monthly serving totals because throughput evidence is missing.

Scroll horizontally to read every chart label and value.

DigitalOcean, GPU Droplets: $1.57, on demand GPU-hour rate, captured 2026-08-08 (1 day ago). Cheapest: RunPod, Community Cloud: $0.74, on demand GPU-hour rate, captured 2026-08-08 (1 day ago). RunPod, Secure Cloud: $0.77, on demand GPU-hour rate, captured 2026-08-08 (1 day ago). Verda: $1.04, on demand GPU-hour rate, captured 2026-08-08 (1 day ago).

  • DigitalOcean, GPU Droplets$1.57
  • Cheapest: RunPod, Community Cloud$0.74
  • RunPod, Secure Cloud$0.77
  • Verda$1.04
Source:
  • DigitalOcean, GPU Droplets, on demand, 1 day ago, captured 2026-08-08
  • RunPod, Community Cloud, on demand, 1 day ago, captured 2026-08-08
  • RunPod, Secure Cloud, on demand, 1 day ago, captured 2026-08-08
  • Verda, on demand, 1 day ago, captured 2026-08-08
+What this chart means

These are GPU-hour rental prices only. A monthly serving total requires throughput evidence and remains absent.

Reproduce with vLLM

The exact command attached to this result.

vllm serve 'Qwen/Qwen2.5-7B-Instruct' --dtype float16 --tensor-parallel-size 1 --max-model-len 8192 --gpu-memory-utilization 0.9

Not measured on this config yet

No site-wide multiplier is applied. Run the exact configuration to create a receipt before comparing its measured baseline with RunInfra.

Run this configuration

Sources and caveats

Every published number keeps its source and date.

Provenance

  • Hugging Face model API revision sha

    As of 2026-08-08

  • Hugging Face model API safetensors.total

    As of 2026-08-08

  • config.json:max_position_embeddings

    As of 2026-08-08

  • config.json:architectures[0]

    As of 2026-08-08

  • NVIDIA RTX 6000 Ada Generation datasheet

    As of 2026-08-08

  • Hugging Face config.json transformer shape

    As of 2026-08-08

  • RunInfra Engine feasibility runtime-overhead policy

    As of 2026-08-09

  • Decode ceiling derived from GPU memory bandwidth and model weight bytes

    As of 2026-08-08

  • vLLM serve CLI documentation

    As of 2026-08-08

  • NVIDIA L4 product specification

    As of 2026-08-08

  • NVIDIA A10 datasheet

    As of 2026-08-08

  • NVIDIA L40S product specification

    As of 2026-08-08

  • NVIDIA A100 product specification

    As of 2026-08-08

Caveats

  • +Served context is 8192 tokens. It is a serving-capacity decision and is not inferred from average input or output tokens.
  • +KV cache uses the exact transformer-shape formula with 28 layers, 4 KV heads, and head dimension 128.
  • +Runtime overhead adds 2.36 GB to totalRequiredGb. This approximate 15% policy allowance covers CUDA context, activations, and vLLM overhead. Deployment-time profiling, including CUDA graph capture and allocator behavior, can differ.
  • +Bandwidth decode CEILING, not expected throughput. Ideal tensor-parallel scaling is assumed. Real decode throughput is lower.
  • +No dense compute ceiling is cited for fp16 on NVIDIA RTX 6000 Ada 48 GB. The available physics bound is decode-only, so the entry point returns no cost instead of copying decode throughput into the input field.
  • +CalcInput has no GPU provider selector. The calculation uses the lowest supplied on-demand rate for RTX-6000-Ada: RunPod, Community Cloud at $0.74/GPU-hour.

Share this calculation

Embed code appears only when the calculator can publish a sourced cost for a fitting configuration.

Badge unavailable for this configuration

The calculator does not have a complete throughput source for this workload, so it withheld the cost and does not generate embed code.

Use it from an agent or script

GET the current inputs, or inspect the descriptor for accepted parameters and response fields.

Endpoint
GET https://runinfra.ai/api/calchttps://runinfra.ai/api/calc?hfId=Qwen%2FQwen2.5-7B-Instruct&gpuId=RTX-6000-Ada&gpuCount=1&requestsPerDay=50000&avgInputTokens=500&avgOutputTokens=500&utilization=0.3&quantization=fp16
Canonical result
https://runinfra.ai/calc/qwen-2.5-7b/rtx-6000-ada/50k-req-day?context=8192
Descriptor
https://runinfra.ai/api/calc/schema

28 GPU ids, 7 quantizations

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