ConwayResearch/Underdog-Saluki-27B-1.0

Name: ConwayResearch/Underdog-Saluki-27B-1.0
Creator: ConwayResearch
License: apache-2.0

text-generationggufVerified checksumsggufllama.cpp2-bittool-callingfunction-callingagents

License: apache-2.0
Size: 8.8 GB
Revision: main
Downloads in the last 30 days: 0 / 30 days

Mirrored from ConwayResearch/Underdog-Saluki-27B-1.0

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Underdog Saluki 27B 1.0

Qwen3.8-27B in under 8 GB, tuned to keep tool calling intact. A standard GGUF for stock llama.cpp. Read more: underdog.ai/saluki

Try Saluki today in underdog.ai


Base model	Qwen3.8-27B
File	`Underdog-Saluki-27B-1.0-IQ2-mix.gguf`, 7.89 GB
Runtime	stock llama.cpp, and apps built on it
Modality	text, plus images with the optional vision add-on
Vision add-on	`mmproj-Underdog-Saluki-27B-1.0-F16.gguf` (928 MB) or `-Q8_0.gguf` (629 MB)
Thinking	on by default, switchable per request, same as Qwen3.8

Quickstart

Add vision. Download the vision add-on too, and pass it with --mmproj. Then send images through the OpenAI chat API as usual.

--jinja turns on the Qwen3.8 chat template, which handles tool calls and thinking. The server speaks the OpenAI chat API on port 8080.

Use	Settings
General use, reasoning, instructions	thinking on (default), temperature 0.6, top_p 0.95, top_k 20
Fast, direct tool calls	thinking off with `"chat_template_kwargs": {"enable_thinking": false}`, temperature 0

Benchmarks

Saluki ran in stock llama.cpp. Where we ran the full-size Qwen3.8-27B ourselves, it used the same harness and settings.

Tool calling. Underdog Bench is 120 tasks from the Berkeley Function Calling Leaderboard (BFCL v4), frozen before any model was tested. Thinking off, temperature 0.

Parallel tool calls. 100 BFCL v4 parallel tasks, official checker, thinking off: Saluki 42, full size 35.

Agents, instructions, coding and reasoning.

Benchmark	Saluki	Full size
SWE-bench Verified (50 issues fixed)	30	33
IFEval (prompt-loose)	93.5	91.5 (public)
IFBench (prompt-loose)	72.7	71.0 (public)
MBPP+	78.0	83.9 (public)
MuSR	67.5	79.6 (public)
AIME 2025 (avg@4)	79.2	96.7 (public)
AIME 2026 (avg@4)	80.0	94.6 (public)

Public scores come from a different harness than ours. 120 tasks is a modest test, and a few tasks of any gap is run-to-run variation.

Limitations

Keeps about 82 to 85% of the full model's competition math score.
Weakest on letter-level instruction puzzles (palindromes, vowel rules, alphabetical order).
About a fifth of parallel-call replies have small formatting slips.
With thinking on, it often reasons at length before answering.
Vision is an add-on. The main file is text only; add the 0.6 to 0.9 GB vision file when you need images.

Credits and license

Apache 2.0. Built on Qwen3.8-27B by the Qwen team and Qwen3.8-27B-GSQ-RCO-GGUF by ISTA-DASLab, both Apache 2.0. Underdog Bench tasks come from the Berkeley Function Calling Leaderboard. See NOTICE.

Built by Underdog.