Qwen 3.6 27B on 16GB: RTX 5060 Ti 16GB vs RX 9060 XT 16GB by Quant (2026)

Per-quant VRAM table: which Qwen 3.6 27B quant fits in 16GB?

GGUF file sizes come from the unsloth/Qwen3.6-27B-GGUF file listing. VRAM columns are computed, not measured. Each is the file size converted to GiB, plus the KV cache from config.json (0.5 GiB at 8K and 2.0 GiB at 32K in f16), about 0.15 GiB of linear-attention state, and about 0.6 GiB of llama.cpp compute buffer. The fit test is against 15.48 GiB, the usable memory per RTX 5060 Ti 16GB after the driver reserve, as reported in LLMKube's dual-5060 Ti Qwen 3.6 27B bake-off. If the same card also drives your desktop, subtract a few hundred MB more.

Unsloth publishes neither a plain Q2_K nor an IQ3_XS for this model. UD-Q2_K_XL and UD-IQ3_XXS are the closest files it ships. If you also load the vision projector (mmproj-BF16.gguf, 0.93 GB), add about 0.9 GiB to every row. That one change can drop UD-Q3_K_XL and IQ4_XS from "fits" to "offload."

Per-quant throughput table: RTX 5060 Ti 16GB vs RX 9060 XT 16GB

Here is the honest state of the public data as of October 2026. Nobody has published a single-card llama-bench run of Qwen 3.6 27B on either card. The closest measured data points are listed below, each with its source, along with the bandwidth ceiling each card can reach on each quant. A ceiling is memory bandwidth divided by file size. It is a physical upper bound, not a measurement, and real llama.cpp generation typically reaches 60–80% of it.

What the data does tell you:

• The 27B-class sibling run is the best proxy. Qwen 3.8 27B is a later model of the same dense 27B size. On a single 5060 Ti, a 13.27 GB 4-bit file generated 24.9 tok/s, which is 74% of the card's 33.8 tok/s ceiling for that file size. Apply the same efficiency to Qwen 3.6 27B Q3_K_M and you would expect roughly 24 tok/s on the 5060 Ti and roughly 17 tok/s on the 9060 XT. Treat those as projections until someone publishes the run.
• The 14B rows disagree with the spec sheet. Those rows show the 9060 XT matching the 5060 Ti at 14B, even though the AMD card has 29% less bandwidth. They came from different harnesses (llamafile vs a recent llama.cpp Vulkan build), so read them as "both cards are close at 14B," not as the 9060 XT winning. The 9060 XT figure works out to about 94% of its bandwidth ceiling, which is unusually high. Expect the gap to widen as model size grows and the run becomes purely bandwidth-bound.

Spec delta: why the two 16GB cards diverge on a 27B model

Sources: NVIDIA's RTX 5060 family page (180W total graphics power) and Tom's Hardware's RTX 5060 Ti 16GB review (448 GB/s, $429 MSRP). AMD's RX 9060 XT page gives the 320 GB/s and 160W figures, and Tom's Hardware's launch report gives the $349 MSRP for the 16GB model. RTX 3060 figures are from the TechPowerUp GPU database. These are launch prices. The live price buttons on this page show today's prices.

The rule for local LLMs is simple. Capacity decides which quant you can run, and bandwidth decides how fast it generates. Both cards have the same 16GB, so they can run exactly the same quants (the VRAM table applies to both). Every generated token reads nearly all of the weights once, so generation speed scales with bandwidth: 448 versus 320 GB/s, a 1.4x advantage for the 5060 Ti on paper. The 9060 XT's 32 MB Infinity Cache does not change this much. A 13 GB weight file does not fit in a 32 MB cache.

Prefill vs generation: where does the RX 9060 XT lose ground?

Prefill (prompt processing) is compute-bound, not bandwidth-bound. It sets how long you wait before the first token appears, and with long prompts it is often the more noticeable delay.

At 14B the 5060 Ti leads prefill by about 10%, which is far smaller than its generation-bandwidth advantage. The 3060 trails both by roughly 40%. The parsapp sweep also found that ROCm and Vulkan tie on 9060 XT prefill, while Vulkan wins generation by 8.8% (33.5 vs 30.8 tok/s). For an RX 9060 XT, start with llama.cpp's Vulkan build and only try ROCm if you need a ROCm-only tool. AMD's community scoreboard in the llama.cpp ROCm performance discussion is the place to check whether a newer ROCm release has closed the gap.

Attention cost on the 16 full-attention layers grows with context, so prefill gets slower per token as prompts get longer and becomes the bottleneck at 32K. On the 27B sibling run, 888 tok/s means a 5,000-token prompt takes about 5.6 seconds before generation starts. A 30,000-token prompt would take at least 34 seconds even at that rate, and longer in practice. That is the real cost of long context on these cards, on top of the VRAM it uses.

How much context fits beside the weights?

Context cost for Qwen 3.6 27B, derived from its config.json (16 full-attention layers × 4 KV heads × 256 head size × K and V):

The main lever is --cache-type-k q8_0 --cache-type-v q8_0 (with flash attention on). It roughly halves the cache, and that is what lets Q3_K_M run at 32K on a 16GB card. q8_0 KV is widely considered close to lossless for chat. q4_0 KV saves more, and the 64K sibling run above used it, but it has a measurable cost on long-context retrieval tasks. Our KV-cache quantization deep dive covers that trade-off on the MoE sibling. Use f16 or q8_0 when exact recall over the whole window matters (code review, contract search), and save q4_0 for long-chat workloads that can tolerate it.

What does the RTX 3060 12GB baseline lose?

The ZOTAC Gaming GeForce RTX 3060 Twin Edge OC 12GB and the MSI GeForce RTX 3060 Ventus 2X 12G have 12 GiB of VRAM, so the largest Qwen 3.6 27B quant they can hold at 8K is about UD-IQ3_XXS or Q3_K_S, with little room left for context.

On the same LocalScore harness, the 5060 Ti generates 24% faster than the 3060 at 14B, which matches their bandwidth ratio (448/360). The bigger loss on the 3060 is quality, not speed. You are stuck at the bottom of the 3-bit range with almost no room for context. Our RX 9060 XT 16GB vs RTX 3060 12GB comparison shows the same pattern on 14B models. The full per-card median across published runs is on /benchmarks/nvidia-geforce-rtx-3060-12-gb.

When 12GB is still right: if you already own a 3060 and mostly run 7–14B models at Q4–Q6, a 16GB upgrade buys speed, not new capability. Spend the money only if 27B-class models are your daily driver.

Perf-per-dollar and perf-per-watt

There is no published Qwen 3.6 27B run on either card, so this uses the most comparable measured numbers: 14B Q4_K_M generation from the sources above, divided by launch MSRP and rated board power. Rated board power is the spec-sheet figure, not measured draw. Generation is bandwidth-bound and usually draws less than the rating.

At 14B the 9060 XT gives you the most tokens per launch dollar and per rated watt. At 27B, expect the 5060 Ti's bandwidth lead to show up in absolute speed. Based on the ceilings, the 5060 Ti's lead should grow toward 1.4x, which is more than its 23% higher MSRP. The value ranking can flip at 27B, and the first published single-card Qwen 3.6 27B runs will settle it. Street prices for these cards change weekly, so check the live price buttons rather than relying on launch MSRP.

Verdict matrix

Get the RTX 5060 Ti 16GB if…

• 27B dense models are your main workload and generation speed matters. Its 448 GB/s gives it a 40% higher ceiling on every quant.
• You want the most mature software. CUDA builds of llama.cpp, vLLM and ExLlama all support Blackwell, and NVFP4 checkpoints such as the one LLMKube ran under vLLM are an option.
• You plan to add a second card later. LLMKube's dual-5060 Ti setup ran Q4_K_M across 32GB.

Get the RX 9060 XT 16GB if…

• Your budget is tight and you mostly run 7–14B models, where the measured gap is negligible.
• You are on Linux and comfortable with llama.cpp's Vulkan backend.
• Perf-per-watt matters for an always-on box. 160W typical board power is the lowest of the three cards.

Stay on a 3060 12GB if…

• You already own one and your models are 14B or smaller.
• You only need Qwen 3.6 27B occasionally and can accept 2–3-bit quants with short context.

Recommended pick

For Qwen 3.6 27B specifically, choose a 5060 Ti: either the ASUS Prime GeForce RTX 5060 Ti 16GB OC Edition, a compact SFF-ready card, or the MSI GeForce RTX 5060 Ti 16G Ventus 2X OC Plus, a two-fan design. The deciding spec is memory bandwidth, 448 versus 320 GB/s. At this model size every token is a full read of 13–14 GB of weights, so bandwidth is the speed limit. If you also do a lot of 7–14B work, or the price gap is wide when you check, the ASUS Dual Radeon RX 9060 XT 16GB is the value pick. The proposal also named the ASRock RX 9060 XT Challenger, which we couldn't match to a catalog listing; the ASRock Radeon RX 9060 XT Steel Legend 16GB is the in-catalog ASRock option with the same 16GB and 320 GB/s memory. All four cards hold the same quants. Only the speed differs.

Bottom line

16GB is the lowest tier where Qwen 3.6 27B runs fully on the GPU at a usable 3-bit quant with real context: Q3_K_M at 8K, or at 32K with q8_0 KV. The RTX 5060 Ti 16GB should generate about 1.4x faster than the RX 9060 XT on this model because of bandwidth. The RX 9060 XT is the better-value card on smaller models. Neither card holds Q4_K_M without offload. If you need 4-bit or better plus long context, plan for 24GB.

Related guides:

• Which GPU for which model: per-LLM VRAM picker
• Qwen 3.6 27B quantization showdown
• RX 9060 XT 16GB vs RTX 3060 12GB for local LLMs
• IBM Granite 4.1 8B vs Qwen 3.6 27B on a 16GB GPU
• Best GPUs for running LLMs locally in 2026

Live price comparison

See current prices for both cards side by side at RTX 5060 Ti 16GB vs RX 9060 XT 16GB.

Citations and sources

All sources accessed 2026-10-08.

• Qwen/Qwen3.6-27B config.json (Hugging Face): layer count, attention layout, KV heads
• unsloth/Qwen3.6-27B-GGUF (Hugging Face): GGUF file sizes
• NVIDIA GeForce RTX 5060 family: RTX 5060 Ti power
• Tom's Hardware: RTX 5060 Ti 16GB review: bandwidth, MSRP
• AMD Radeon RX 9060 XT: bandwidth, board power, memory
• Tom's Hardware: RX 9060 XT launch: 16GB MSRP
• TechPowerUp: GeForce RTX 3060 12 GB: RTX 3060 specs
• LocalScore: RTX 5060 Ti and LocalScore: RTX 3060: 14B prefill/generation
• parsapp/rx9060xt-llm-benchmarks: RX 9060 XT Vulkan vs ROCm
• llama.cpp ROCm performance discussion #15021: AMD scoreboard
• LLMKube: Qwen3.6-27B on dual RTX 5060 Ti: usable VRAM per card, dual-card runs
• Paul's Programming Notes: Qwen 3.8 27B on a 16 GB GPU: 27B-class single-5060 Ti run

This article is an editorial synthesis of the published specifications and third-party benchmarks cited above. SpecPicks did not run these cards. VRAM figures and throughput ceilings are calculated from the cited sources and labeled as such. Where no public run exists, the tables say so rather than estimate.