RTX 5060 Ti 8GB vs RTX 5060 Ti 16GB for local LLMs
Assumes 32 GB of DDR5-5600 system RAM, Windows with this GPU driving the display, 8k context and an f16 KV cache.
What to know before choosing
Both cards use the same chip and memory bandwidth, so speed estimates match whenever a model fits in 8GB. CanRun counts 7.4 GB usable on the 8GB card, 15.4 GB on the 16GB card. Qwen3 8B runs great on both, with little margin on the 8GB card (check ollama ps). Gemma 4 12B outgrows the 8GB card, but with most of it on the GPU it runs well. Gemma 3 12B spills further and runs slowly there, as does Phi-4, which needs 11.0 GB. Both run great on the 16GB card. Both are sold as "RTX 5060 Ti", so check the memory size.
MoE models make system RAM matter too. gpt-oss-20b fits fully only on the 16GB card, a pairing in the public benchmarks below. On the 8GB card some experts go to system RAM; it runs well, a theoretical estimate (±30%). With 32GB of system RAM, Qwen3 30B-A3B (2507) runs well on both (theoretical). With only 16GB of RAM it won't run on the 8GB card, yet the 16GB card runs it well (theoretical).
At 16k with an f16 KV cache, Qwen3 8B needs 7.7 GB, so the 8GB card moves part of it to system RAM. A q8_0 KV cache keeps it on the GPU, and the 16GB card holds 32k fully.
Speed
The RTX 5060 Ti 8GB and the RTX 5060 Ti 16GB generate text at about the same speed (median of our estimates over the 20 models that fit entirely in memory on both at Q4_K_M or the closest available quant).
- Reference model
- Qwen3.5 9B at Q4_K_M, the largest model that fits entirely in memory on both at Q4_K_M or the closest available quant
- RTX 5060 Ti 8GB
- est. 51.1 tok/s (45.0–57.2, calibrated estimate ±12%)
- RTX 5060 Ti 16GB
- est. 51.1 tok/s (45.0–57.2, calibrated estimate ±12%)
- Prompt processing on Qwen3.5 9B
- RTX 5060 Ti 8GB: about 2,588 tok/s (1,553–3,623, rough estimate ±40%); RTX 5060 Ti 16GB: about 2,588 tok/s (1,553–3,623, rough estimate ±40%)
Specs side by side
| Spec | RTX 5060 Ti 8GB | RTX 5060 Ti 16GB | Difference |
|---|---|---|---|
| Memory | 8 GB | 16 GB | +8 GB on the RTX 5060 Ti 16GB |
| Memory bandwidth | 448.0 GB/s | 448.0 GB/s | Same |
| FP16 compute | 23.7 TFLOPS | 23.7 TFLOPS | Same |
| Launch year | 2025 | 2025 | — |
| Price | $429 street (as of 2026-08-09) | $569 street (as of 2026-08-09) | — |
| Public benchmark results | 0 results | 4 results | — |
Verdicts at a glance
Out of 58 models at Q4_K_M (or the closest available quant) with 8k context.
- RTX 5060 Ti 8GBRuns great20 modelsRuns well10 modelsRuns slowly14 modelsWon't run14 models
- RTX 5060 Ti 16GBRuns great28 modelsRuns well9 modelsRuns slowly11 modelsWon't run10 models
How to read the verdicts
- Runs great
- Fully on the GPU at 20 tok/s or more
- Runs well
- Fully on the GPU at 8–20 tok/s; MoE experts in system RAM at 20 tok/s or more; or at least 90% on the GPU at 8 tok/s or more
- Runs slowly
- 2–8 tok/s; CPU-only; less than 90% on the GPU; or MoE experts in system RAM below 20 tok/s
- Won't run
- Does not fit, or under 2 tok/s
Where the verdicts differ
15 models get a different verdict on the two.
Scroll sideways to see every column.
| Model | RTX 5060 Ti 8GB verdict | RTX 5060 Ti 8GB speed | RTX 5060 Ti 16GB verdict | RTX 5060 Ti 16GB speed |
|---|---|---|---|---|
| gpt-oss-20bMXFP4 | Runs well | est. 43.9 tok/s30.7–57.1theoretical estimate ±30% | 111.6 tok/s8k estimate 104.3 tok/s (83.5–125.2, calibrated estimate ±20%)measured (1 run, 2k context) | |
| Kanana 1.5 15.7B-A3BQ4_K_M | Runs well | est. 42.6 tok/s29.8–55.3theoretical estimate ±30% | Runs great | est. 89.1 tok/s71.3–106.9calibrated estimate ±20% |
| Qwen3 14BQ4_K_M | Runs slowly | est. 9.1 tok/s7.3–10.9calibrated estimate ±20% | est. 30.3 tok/s26.7–34.0calibrated estimate ±12% | |
| HyperCLOVA X SEED Think 14BQ4_K_M | Runs slowly | est. 9.4 tok/s6.6–12.2theoretical estimate ±30% | Runs great | est. 30.8 tok/s21.5–40.0theoretical estimate ±30% |
| Phi-4Q4_K_M | Runs slowly | est. 8.1 tok/s6.5–9.8calibrated estimate ±20% | Runs great | est. 29.2 tok/s25.7–32.7calibrated estimate ±12% |
| Gemma 3 12BQ4_K_M | Runs slowly | est. 21.8 tok/s17.5–26.2calibrated estimate ±20% | est. 40.0 tok/s35.2–44.8calibrated estimate ±12% | |
| Mellum2.1 12B-A2.5B ThinkingQ4_K_M | Runs well | est. 94.7 tok/s66.3–123.1theoretical estimate ±30% | Runs great | est. 147.7 tok/s118.2–177.2calibrated estimate ±20% |
| Gemma 4 12BQ4_K_M | Runs well | est. 31.7 tok/s25.4–38.1calibrated estimate ±20% | Runs great | est. 43.2 tok/s38.0–48.4calibrated estimate ±12% |
| K2-Horizon MoVA 36B-A4BQ4_K_M | Runs slowly | est. 9.6 tok/s6.7–12.5theoretical estimate ±30% | Runs well | est. 30.7 tok/s21.5–39.9theoretical estimate ±30% |
| Mistral Small 3.2 24BQ4_K_M | Runs slowly | est. 4.3 tok/s3.4–5.1calibrated estimate ±20% | Runs well | est. 14.8 tok/s11.8–17.7calibrated estimate ±20% |
| DeepSeek R1 Distill Qwen 14BQ4_K_M | Runs slowly | est. 8.4 tok/s6.7–10.1calibrated estimate ±20% | Runs well | est. 29.6 tok/s26.0–33.1calibrated estimate ±12% |
| EXAONE 4.5 33BQ4_K_M | Won't runTry IQ4_XS: Runs slowly | est. 3.4 tok/s2.8–4.1calibrated estimate ±20% | Runs slowly | est. 5.6 tok/s4.5–6.7calibrated estimate ±20% |
| DeepSeek R1 Distill Qwen 32BQ4_K_M | Won't runTry Q2_K (heavy quality loss): Runs slowly | est. 4.6 tok/s3.7–5.5calibrated estimate ±20% | Runs slowly | est. 4.5 tok/s3.6–5.4calibrated estimate ±20% |
| Qwen3 32BQ4_K_M | Won't runTry Q2_K (heavy quality loss): Runs slowly | est. 4.6 tok/s3.7–5.5calibrated estimate ±20% | Runs slowly | est. 4.5 tok/s3.6–5.5calibrated estimate ±20% |
| Granite 4.2 30BQ4_K_M | Won't runTry Q2_K (heavy quality loss): Runs slowly | est. 5.5 tok/s4.4–6.6calibrated estimate ±20% | Runs slowly | est. 5.8 tok/s4.7–7.0calibrated estimate ±20% |
Every model on both
Scroll sideways to see every column.
| Model | RTX 5060 Ti 8GB verdict | RTX 5060 Ti 8GB speed | RTX 5060 Ti 16GB verdict | RTX 5060 Ti 16GB speed |
|---|---|---|---|---|
| gpt-oss-20bMXFP4 | Runs well | est. 43.9 tok/s30.7–57.1theoretical estimate ±30% | 111.6 tok/s8k estimate 104.3 tok/s (83.5–125.2, calibrated estimate ±20%)measured (1 run, 2k context) | |
| Kanana 1.5 15.7B-A3BQ4_K_M | Runs well | est. 42.6 tok/s29.8–55.3theoretical estimate ±30% | Runs great | est. 89.1 tok/s71.3–106.9calibrated estimate ±20% |
| Qwen3 14BQ4_K_M | Runs slowly | est. 9.1 tok/s7.3–10.9calibrated estimate ±20% | est. 30.3 tok/s26.7–34.0calibrated estimate ±12% | |
| HyperCLOVA X SEED Think 14BQ4_K_M | Runs slowly | est. 9.4 tok/s6.6–12.2theoretical estimate ±30% | Runs great | est. 30.8 tok/s21.5–40.0theoretical estimate ±30% |
| Phi-4Q4_K_M | Runs slowly | est. 8.1 tok/s6.5–9.8calibrated estimate ±20% | Runs great | est. 29.2 tok/s25.7–32.7calibrated estimate ±12% |
| Gemma 3 12BQ4_K_M | Runs slowly | est. 21.8 tok/s17.5–26.2calibrated estimate ±20% | est. 40.0 tok/s35.2–44.8calibrated estimate ±12% | |
| Mellum2.1 12B-A2.5B ThinkingQ4_K_M | Runs well | est. 94.7 tok/s66.3–123.1theoretical estimate ±30% | Runs great | est. 147.7 tok/s118.2–177.2calibrated estimate ±20% |
| Gemma 4 12BQ4_K_M | Runs well | est. 31.7 tok/s25.4–38.1calibrated estimate ±20% | Runs great | est. 43.2 tok/s38.0–48.4calibrated estimate ±12% |
| Qwen3.5 9BQ4_K_M | Runs great | est. 51.1 tok/s45.0–57.2calibrated estimate ±12% | Runs great | est. 51.1 tok/s45.0–57.2calibrated estimate ±12% |
| K2-Horizon 7BQ4_K_M | Runs great | est. 46.1 tok/s40.6–51.7calibrated estimate ±12% | Runs great | est. 46.1 tok/s40.6–51.7calibrated estimate ±12% |
| Qwen3 8BQ4_K_M | Runs great | est. 50.3 tok/s44.2–56.3calibrated estimate ±12% | Runs great | est. 50.3 tok/s44.2–56.3calibrated estimate ±12% |
| DeepSeek R1 0528 Qwen3 8BQ4_K_M | Runs great | est. 50.3 tok/s44.2–56.3calibrated estimate ±12% | Runs great | est. 50.3 tok/s44.2–56.3calibrated estimate ±12% |
| DeepSeek R1 Distill Llama 8BQ4_K_M | Runs great | est. 52.3 tok/s46.0–58.6calibrated estimate ±12% | Runs great | est. 52.3 tok/s46.0–58.6calibrated estimate ±12% |
| Kanana 1.5 8BQ4_K_M | Runs great | est. 52.3 tok/s46.0–58.6calibrated estimate ±12% | Runs great | est. 52.3 tok/s46.0–58.6calibrated estimate ±12% |
| Llama 3.1 8BQ4_K_M | Runs great | est. 52.3 tok/s46.0–58.6calibrated estimate ±12% | est. 52.3 tok/s46.0–58.6calibrated estimate ±12% | |
| Gemma 4 E4BQ4_K_M | Runs great | est. 87.2 tok/s61.0–113.3theoretical estimate ±30% | Runs great | est. 87.2 tok/s61.0–113.3theoretical estimate ±30% |
| Ling-3.0 TinyQ4_K_M | Runs great | est. 250.3 tok/s175.2–325.4theoretical estimate ±30% | Runs great | est. 250.3 tok/s175.2–325.4theoretical estimate ±30% |
| Gemma 4 E2BQ4_K_M | Runs great | est. 158.9 tok/s111.2–206.6theoretical estimate ±30% | Runs great | est. 158.9 tok/s111.2–206.6theoretical estimate ±30% |
| Qwen3.5 4BQ4_K_M | Runs great | est. 101.2 tok/s89.1–113.4calibrated estimate ±12% | Runs great | est. 101.2 tok/s89.1–113.4calibrated estimate ±12% |
| Nanbeige4.2 3BQ4_K_M | Runs great | est. 51.2 tok/s35.8–66.5theoretical estimate ±30% | Runs great | est. 51.2 tok/s35.8–66.5theoretical estimate ±30% |
| Spark-X2.5 4BQ4_K_M | Runs great | est. 108.1 tok/s95.1–121.0calibrated estimate ±12% | Runs great | est. 108.1 tok/s95.1–121.0calibrated estimate ±12% |
| Llama 3.2 3BQ4_K_M | Runs great | est. 106.0 tok/s93.2–118.7calibrated estimate ±12% | Runs great | est. 106.0 tok/s93.2–118.7calibrated estimate ±12% |
| LFM2.5 2.6BQ4_K_M | Runs great | est. 173.8 tok/s121.7–226.0theoretical estimate ±30% | Runs great | est. 173.8 tok/s121.7–226.0theoretical estimate ±30% |
| MiniCPM5 2BQ4_K_M | Runs great | est. 164.0 tok/s144.3–183.7calibrated estimate ±12% | Runs great | est. 164.0 tok/s144.3–183.7calibrated estimate ±12% |
| HyperCLOVA X SEED 1.5BQ4_K_M | Runs great | est. 172.8 tok/s152.0–193.5calibrated estimate ±12% | Runs great | est. 172.8 tok/s152.0–193.5calibrated estimate ±12% |
| EXAONE 4.0 1.2BQ4_K_M | Runs great | est. 238.8 tok/s210.1–267.4calibrated estimate ±12% | Runs great | est. 238.8 tok/s210.1–267.4calibrated estimate ±12% |
| Llama 3.2 1BQ4_K_M | Runs great | est. 290.8 tok/s255.9–325.7calibrated estimate ±12% | Runs great | est. 290.8 tok/s255.9–325.7calibrated estimate ±12% |
| MiniCPM5 1BQ4_K_M | Runs great | est. 351.8 tok/s309.6–394.1calibrated estimate ±12% | Runs great | est. 351.8 tok/s309.6–394.1calibrated estimate ±12% |
| K2-Horizon MoVA 36B-A4BQ4_K_M | Runs slowly | est. 9.6 tok/s6.7–12.5theoretical estimate ±30% | Runs well | est. 30.7 tok/s21.5–39.9theoretical estimate ±30% |
| Qwen3.5 35B-A3BQ4_K_M | Runs well | est. 48.3 tok/s33.8–62.8theoretical estimate ±30% | Runs well | est. 62.4 tok/s43.7–81.1theoretical estimate ±30% |
| Qwen3.6 35B-A3BQ4_K_M | Runs well | est. 52.5 tok/s36.7–68.2theoretical estimate ±30% | Runs well | est. 69.5 tok/s48.7–90.4theoretical estimate ±30% |
| MiniCPM-V 4.7 35B-A3BQ4_K_M | Runs well | est. 54.5 tok/s38.2–70.9theoretical estimate ±30% | Runs well | est. 74.7 tok/s52.3–97.1theoretical estimate ±30% |
| Nemotron 3.5 Lightning 30B-A3BQ4_K_M | Runs well | est. 37.3 tok/s26.1–48.5theoretical estimate ±30% | Runs well | est. 50.8 tok/s35.6–66.0theoretical estimate ±30% |
| Qwen3 30B-A3B (2507)Q4_K_M | Runs well | est. 37.1 tok/s26.0–48.3theoretical estimate ±30% | est. 57.7 tok/s40.4–75.1theoretical estimate ±30% | |
| Gemma 4 26B-A4BQ4_K_M | Runs well | est. 37.6 tok/s26.3–48.8theoretical estimate ±30% | Runs well | est. 59.2 tok/s41.4–76.9theoretical estimate ±30% |
| Mistral Small 3.2 24BQ4_K_M | Runs slowly | est. 4.3 tok/s3.4–5.1calibrated estimate ±20% | Runs well | est. 14.8 tok/s11.8–17.7calibrated estimate ±20% |
| DeepSeek R1 Distill Qwen 14BQ4_K_M | Runs slowly | est. 8.4 tok/s6.7–10.1calibrated estimate ±20% | Runs well | est. 29.6 tok/s26.0–33.1calibrated estimate ±12% |
| EXAONE 4.5 33BQ4_K_M | Won't runTry IQ4_XS: Runs slowly | est. 3.4 tok/s2.8–4.1calibrated estimate ±20% | Runs slowly | est. 5.6 tok/s4.5–6.7calibrated estimate ±20% |
| DeepSeek R1 Distill Qwen 32BQ4_K_M | Won't runTry Q2_K (heavy quality loss): Runs slowly | est. 4.6 tok/s3.7–5.5calibrated estimate ±20% | Runs slowly | est. 4.5 tok/s3.6–5.4calibrated estimate ±20% |
| Qwen3 32BQ4_K_M | Won't runTry Q2_K (heavy quality loss): Runs slowly | est. 4.6 tok/s3.7–5.5calibrated estimate ±20% | Runs slowly | est. 4.5 tok/s3.6–5.5calibrated estimate ±20% |
| EXAONE 4.0 32BQ4_K_M | Runs slowly | est. 3.1 tok/s2.5–3.7calibrated estimate ±20% | Runs slowly | est. 6.1 tok/s4.9–7.4calibrated estimate ±20% |
| Gemma 4 31BQ4_K_M | Runs slowly | est. 3.3 tok/s2.7–4.0calibrated estimate ±20% | Runs slowly | est. 7.0 tok/s5.6–8.4calibrated estimate ±20% |
| Muse Glimmer 30BQ4_K_M | Runs slowly | est. 3.9 tok/s3.1–4.6calibrated estimate ±20% | Runs slowly | est. 9.5 tok/s7.6–11.4calibrated estimate ±20% |
| Granite 4.2 30BQ4_K_M | Won't runTry Q2_K (heavy quality loss): Runs slowly | est. 5.5 tok/s4.4–6.6calibrated estimate ±20% | Runs slowly | est. 5.8 tok/s4.7–7.0calibrated estimate ±20% |
| Qwen3.5 27BQ4_K_M | Runs slowly | est. 3.7 tok/s3.0–4.4calibrated estimate ±20% | Runs slowly | est. 8.9 tok/s7.1–10.7calibrated estimate ±20% |
| Qwen3.6 27BQ4_K_M | Runs slowly | est. 3.8 tok/s3.0–4.6calibrated estimate ±20% | Runs slowly | est. 9.5 tok/s7.6–11.4calibrated estimate ±20% |
| Qwen3.8 27BQ4_K_M | Runs slowly | est. 3.6 tok/s2.9–4.3calibrated estimate ±20% | Runs slowly | est. 8.4 tok/s6.7–10.0calibrated estimate ±20% |
| Gemma 3 27BQ4_K_M | Runs slowly | est. 3.8 tok/s3.1–4.6calibrated estimate ±20% | Runs slowly | est. 9.7 tok/s7.8–11.7calibrated estimate ±20% |
| GLM-5.3 FlashQ4_K_M | Won't run | — | Won't run | — |
| DeepSeek V4 Flash 0731MXFP4 | Won't run | — | Won't run | — |
| Solar Open 2 250BIQ4_XS | Won't run | — | Won't run | — |
| Ling-3.0 FlashQ4_K_M | Won't run | — | Won't run | — |
| Qwen3.5 122B-A10BQ4_K_M | Won't run | — | Won't run | — |
| Laguna S 2.1Q4_K_M | Won't run | — | Won't run | — |
| gpt-oss-120bMXFP4 | Won't run | — | — | |
| Solar Open 100BQ4_K_M | Won't run | — | Won't runTry Q2_K (heavy quality loss): Runs slowly | est. 18.7 tok/s13.1–24.4theoretical estimate ±30% |
| Kolibri 1Q4_K_M | Won't runTry Q2_K (heavy quality loss): Runs well | est. 55.3 tok/s38.7–71.9theoretical estimate ±30% | Won't runTry Q2_K (heavy quality loss): Runs well | est. 63.3 tok/s44.3–82.3theoretical estimate ±30% |
| Llama 3.3 70BQ4_K_M | Won't run | — | Won't runTry Q2_K (heavy quality loss): Runs slowly | est. 2.5 tok/s2.0–3.1calibrated estimate ±20% |
Models with a thinking mode spend extra tokens thinking, so their speed thresholds are 1.5× stricter (30 / 12 / 3 tok/s). With thinking turned off, a model may do one grade better.
Public benchmarks
Measured results on the RTX 5060 Ti 8GB
No public measurements for this device yet.
Measured results on the RTX 5060 Ti 16GB
| Model | Quant | Backend | Context | Prompt (tok/s) | Generation (tok/s) | Flags | Source | Measured |
|---|---|---|---|---|---|---|---|---|
| llama-2-7b | Q4_0 | llama.cpp | 512 | 3,737.0 | 90.9 | — | github.com | 2025-08-02 |
| gpt-oss-20b | MXFP4 | llama.cpp | 2k | 3,821.0 | 111.6 | — | github.com | 2025-08-20 |
| Qwen3.8 27B | UD-IQ4_XS | llama.cpp | 8k | — | 27.6 | KV q8_0 | github.com | 2026-10-11 |
| Qwen3 8B | Q4_K_XL | llama.cpp | 4k | 2,965.0 | 69.2 | CUDA | hardware-corner.net | 2025-12-09 |
Public benchmarks we calibrate against. Their conditions (context, backend, flags) can differ from the estimates above.
Frequently asked questions
Which is faster for local LLMs, the RTX 5060 Ti 8GB or the RTX 5060 Ti 16GB?
The RTX 5060 Ti 8GB and the RTX 5060 Ti 16GB generate text at about the same speed (median of our estimates over the 20 models that fit entirely in memory on both at Q4_K_M or the closest available quant). Estimated speed on Qwen3.5 9B at Q4_K_M: the RTX 5060 Ti 8GB est. 51.1 tok/s (45.0–57.2, calibrated estimate ±12%); the RTX 5060 Ti 16GB est. 51.1 tok/s (45.0–57.2, calibrated estimate ±12%).
What is the largest model each can run entirely in memory?
The RTX 5060 Ti 8GB fits Gemma 4 12B at IQ4_XS (6.38 GB file) entirely in 8 GB, at est. 48.1 tok/s (42.4–53.9, calibrated estimate ±12%). The RTX 5060 Ti 16GB fits Muse Glimmer 30B at IQ4_XS (15.44 GB file) entirely in 16 GB, at est. 20.2 tok/s (17.7–22.6, calibrated estimate ±12%).
How many local LLMs run well on each?
At Q4_K_M with 8k context, out of 58 tracked models: the RTX 5060 Ti 8GB — 20 Runs great, 10 Runs well, 14 Runs slowly, 14 Won't run; the RTX 5060 Ti 16GB — 28 Runs great, 9 Runs well, 11 Runs slowly, 10 Won't run. 15 models get a different verdict.
Speeds are estimates from memory bandwidth, calibrated against public benchmarks, and each one comes with an error band and a confidence label. Real results vary with drivers, backend, context length and thermals.