Tested >200k context on 2 RTX 3090's (48GB VRAM)

#9
by Mick277 - opened

DavidAU/Qwen3.6-27B MTP Q8_0 GGUF

Prompt eval 244 s / 202569 tokens at 828.62 tokens per sec
prompt response 32 s / 1637 tokens 49.94 tokens per sec
Had to reduce max context to 220k for 94% of VRAM. At 262K it crashed with out of memory.

For comparison:

Unsloth/Qwen3.6 35B A3B UD MTP Q8_K_XL GGUF
Prompt eval 173 s / 202563 tokens at 1166.16 tokens per sec
prompt response 35 s / 1573 tokens 44.81 tokens per sec

This version of Qwen3.6 27B isn't much slower than Qwen3.6 35B A3B overall, it makes the GPU's work harder and they get hotter. The results seem a little better than Qwen3.6 35B A3B from a few initial tests.

DavidAU/Qwen3.6-27B MTP Q8_0 GGUF

Prompt eval 244 s / 202569 tokens at 828.62 tokens per sec
prompt response 32 s / 1637 tokens 49.94 tokens per sec
Had to reduce max context to 220k for 94% of VRAM. At 262K it crashed with out of memory.

For comparison:

Unsloth/Qwen3.6 35B A3B UD MTP Q8_K_XL GGUF
Prompt eval 173 s / 202563 tokens at 1166.16 tokens per sec
prompt response 35 s / 1573 tokens 44.81 tokens per sec

This version of Qwen3.6 27B isn't much slower than Qwen3.6 35B A3B overall, it makes the GPU's work harder and they get hotter. The results seem a little better than Qwen3.6 35B A3B from a few initial tests.

Why are you comparing this to the moe model? What about the original 27b?

@joonanykanen

To clarify, the base 35B-A3B Qwen 3.6 is STRONGER than the base Qwen 3.6 27B.
This may be why @Mick277 did the comparison this way.

wait - really? I thought the dense model Is the better one?
@DavidAU

@psychofanPLAYS

It (27B dense base) is stronger for some tasks, but I found for certain other tasks - specifically using knowledge in a user case specific situations such as synthetic, "intelligent" generation based on knowledge -
it can eclipse the "base" Qwen 3.6 27B.

The "711" however trumps the 35B-A3B.

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