Skip to main contentThe Local Bench

GeForce RTX 4060 Ti 16 GB

NVIDIA · Discrete GPU · as of 2026-10-12

Specs sourced · published reference runs · catalogue speeds mostly estimated
Discrete graphics card
  • Data checked: 2026-10-12. Review interval shown below. Prices need review after 30 days; specifications and benchmark collections after 90 days. Dates describe the recorded check, not a live retailer quote.

    • Verified Checked against the primary source (for example the model’s config.json on Hugging Face).
    • Sourced Taken from a cited source; not yet independently checked.
    • Estimate Calculated with the published formulas; not a measurement.
    • Sample Placeholder data for layout; not a real figure.
    • Not yet measured No public, citable score found for this benchmark yet. We never fill the gap with a guess.

    Verified metadata is not a measured performance result. Only cited runs matching model, device, quant and recorded context can replace speed estimates. Estimates assume one stream and F16 KV cache, with a ±25% uncertainty band. A published run applies only to its recorded runtime and conditions; missing settings are unknown.

    • llama-2-7b · rtx-4060-ti-16g
      llama.cpp (CUDA) · Q4_0 · tg128
      Recorded 2026-10-12 · historical source record · repeat count unknownSourced
      Llama 2 7B Q4_0, llama-bench tg128, full GPU offload, flash attention off, single GPU. Community scoreboard entry; commit and submitter in the source table. Measured on the 8 GB variant (same 288 GB/s bus); treat as indicative for the 16 GB card. Run source

    Evidence labels · Freshness policy · Calculation methodology

16GB
memory, 15.5 GB usableSourced
288GB/s
memory bandwidthSourced
$844.37
price, USDEstimate
4of 10
catalogue models fit at 8k

Cheapest new 16 GB card. Narrow 128-bit bus caps decode speed.

Decode-speed ceiling for a model is 288 GB/s ÷ GB read per token. For a 16.6 GB file that is 17 tok/s; real runtimes reach roughly 60% of it. Why bandwidth is the limit.

In builds: Silent home server

See every model on this device

Specifications

Memory
16 GBSourced16 GB variant, nvidia.com, checked 2026-10-12. Source
Bandwidth
288 GB/sSourcedNVIDIA's GeForce spec pages list bus width but not bandwidth; figure from the cited Wikipedia spec table (bus width cross-checked on nvidia.com, 2026-10-12). Source
FP16 dense compute
44 TFLOPSSampleSample FP16 dense compute; pending vendor-sheet citation.
Host RAM (offload)
32 GBSampleAssumed host RAM for offload.
Vendor TDP / board power
165 WSourcedTotal Graphics Power (16 GB variant), nvidia.com. Source
Load power at wall
230 WSampleSample wall power under load.
Price, USD
$844.37EstimateNo valid new 16 GB listing found on Newegg US; Newegg Canada price ÷ 1.4271 (Bank of Canada). Source
Price, CAD
CA$1,205SourcedLowest new in-stock 16 GB listing on Newegg Canada (MSI Gaming). Checked 2026-10-12. Source

Models that run

Default quant, single stream, 8k context. Fastest first; estimates are ±25% until measured.

Model
Quant
Memory
Verdict
Decode, tok/s
Max context
gpt-oss-20bMXFP412.9 GBFits75.5Estimate64k
Qwen3 30B-A3BQ4_K_M19.9 GBNeeds offload35.1Estimate—
Llama 3.1 8B InstructQ4_K_M6.6 GBFits28.8Estimate64k
Qwen3 8BQ4_K_M6.8 GBFits27.7Estimate32k
Qwen3 14BQ4_K_M10.9 GBFits16.7Estimate32k
Mistral Small 3.2 24BQ4_K_M16.2 GBNeeds offload9.1Estimate2k
Gemma 3 27B ITQ4_K_M18.2 GBNeeds offload5.8Estimate—
Qwen3 32BQ4_K_M22.5 GBNeeds offload3.3Estimate—
Llama 3.3 70B InstructQ4_K_M45.8 GBDoes not fit——
gpt-oss-120bMXFP464.3 GBDoes not fit——

Published reference runs

Third-party llama.cpp measurements on this device, with conditions and source. Llama 2 7B Q4_0 runs are the community calibration test; they are not catalogue models.

Model
Quant
Date
Runtime · test
Decode, tok/s
Conditions
llama-2-7bQ4_02026-10-12llama.cpp (CUDA) · tg12863.9SourcedLlama 2 7B Q4_0, llama-bench tg128, full GPU offload, flash attention off, single GPU. Community scoreboard entry; commit and submitter in the source table. Measured on the 8 GB variant (same 288 GB/s bus); treat as indicative for the 16 GB card. Source

Usable memory: discrete VRAM − 0.5 GB reserve; unified RAM × 0.75; fits when total ≤ 90% of usable (concept brief §7.3). Markdown · JSON