Model × hardware

Can NVIDIA GeForce RTX 5060 Ti 16GB run Qwen2.5-7B-Instruct-1M?

Qwen2.5-7B-Instruct-1M at Q4_K_M fits the estimated NVIDIA GeForce RTX 5060 Ti 16GB memory budget at 4,096 tokens: 5.58 GiB required versus 14.40 GiB usable. 38.3–76.5 estimated tokens/s.

Selected formatQ4_K_M
Estimated requirement5.58 GiB
Usable device memory14.40 GiB
Estimated headroom8.82 GiB
Adjust this setup ↗Hardware details

Compare the recorded formats.

One sequence, default context up to 4,096 tokens; 90% memory budget
QuantWeight filesEstimated KVEstimated totalFitEstimated generation
Q4_K_M4.36 GiB0.22 GiB5.58 GiBfits38.3–76.5 estimated tokens/s
Q8_07.54 GiB0.22 GiB8.76 GiBfits22.1–44.3 estimated tokens/s

What changes with a longer context?

Q4_K_M; constant weights, growing estimated cache
Context tokensEstimated KVEstimated totalFit
2,0480.11 GiB5.47 GiBfits
4,0960.22 GiB5.58 GiBfits
8,1920.44 GiB5.80 GiBfits
16,3840.88 GiB6.24 GiBfits
32,7681.75 GiB7.11 GiBfits

The formula for this estimate.

Weights GiB = exact recorded file bytes / 2^30. KV GiB = 2 × layers × KV heads × head dimension × context × KV bytes / 2^30. Required GiB = weights + KV + runtime overhead. Usable GiB = device GiB × usable fraction. Estimated decode tokens/s = bandwidth GB/s × 10^9 / (active parameters B × 10^9 × effective bytes per weight) × efficiency. Effective bytes per weight = file bytes / (total parameters B × 10^9). Selected efficiency = 0.6; sensitivity uses 0.4–0.8.

Assumptions and limitations
  • Memory values labeled GB in the data contract are GiB (2^30 bytes); bandwidth uses decimal GB/s (10^9 bytes/s).
  • The memory budget reserves 10.0% of device memory. Runtime overhead is an assumed 1 GiB.
  • KV cache assumes 2 bytes per element, independently of weight quantization. Runtime cache layout and allocation can add memory.
  • Memory fit does not establish runtime, driver, operating-system, architecture, or quantization support.
  • All speed values are estimated single-stream decode proxies, not benchmarks. Prefill, batching, latency, and concurrent sessions are not predicted.
  • Estimated speed sensitivity is not a confidence interval; actual speed can fall outside the range because of compute, cache traffic, kernels, thermal limits, and other workloads.
  • Effective bytes per weight is the exact file-size / total-parameter proxy. Metadata, tensors with different precision, padding, and duplicated tensors make it different from nominal quantization bits.

Source records

Official model metadata · Exact weight files · Maker hardware specifications

Model verified 2026-10-22; hardware verified 2026-10-22. This is an estimated memory and bandwidth calculation, not a hands-on benchmark.