Unsloth · Qwen 3.6

Qwen 3.6 35B A3B GGUF

Verified by Badgr · Serve

Qwen 3.6 35B A3B GGUF is a 34.7B chat and text-generation model available through supported Badgr execution routes.

Last validated or meaningfully updated: 2026-10-09

ChatLong contextFine-tunable

✓ Verified by Badgr · llama.cpp · Serve

Last verified 2026-10-09

badgr serve --runtime llama.cpp --hf-repo unsloth/Qwen3.6-35B-A3B-GGUF --hf-file Qwen3.6-35B-A3B-UD-IQ4_XS.gguf --gpu auto --max-cost 3 --startup-timeout 50
GPU
NVIDIA GeForce RTX 3090Reported by the provider, not confirmed inside the container
Time to verified
186.1s
Deployment
dep-03c936ee8b
  • ✓ llama-server started
  • ✓ /health returned HTTP 200
  • ✓ Tool-calling requests returned parsed tool_calls
  • ✓ final_state = VERIFIED
  • ✓ Teardown completed

A 17.7 GB model: Badgr sizes the startup window to the file, so the download is not abandoned mid-way. In 24 requests with the payload from ggml-org/llama.cpp#30118, 7 returned parsed tool_calls and none leaked <function=...> text into the message content.

GitHub issue this run was for: ggml-org/llama.cpp#30118

Raw evidence
final_state=VERIFIED failure_class=None providers_tried=1 spend_usd=0.0147 elapsed=186.1s

Run from Badgr's local development environment. Documents that this deployment path works end-to-end for this model.

✓ Verified by Badgr · Ollama · Serve

Last verified 2026-10-09

badgr serve qwen3.6:35b --runtime ollama --gpu auto --max-cost 2 --startup-timeout 40
GPU
NVIDIA A40Reported by the provider, not confirmed inside the container
Time to verified
158s
Deployment
dep-ab1f15ad47
  • ✓ Ollama server started
  • ✓ /api/tags listed qwen3.6:35b
  • ✓ A 10,101-token /api/chat request with num_ctx 65536 returned a reply
  • ✓ final_state = VERIFIED
  • ✓ Teardown completed

This is the Ollama library tag qwen3.6:35b (22.6 GB), not the Unsloth GGUF file used by the llama.cpp entry. A request with a 65,536-token context and a 10,101-token prompt completed. The elapsed time is estimated from the spend at verification and the hourly rate.

GitHub issue this run was for: ollama/ollama#18856

Raw evidence
final_state=VERIFIED failure_class=None providers_tried=1 spend_usd=0.02

Run from Badgr's local development environment. Documents that this deployment path works end-to-end for this model.

Availability

Not yet Badgr AI API

Not currently validated

✓ Dedicated endpoint

Available through Badgr

✓ Custom GPU deployment

Available through Badgr

Deployment profile

Architecture
qwen35moe (GGUF)
Licence
Apache-2.0
Minimum VRAM
~74GB
Context
256K tokens

Recommended: A100 80GB. VRAM is an estimate and increases with context, cache, concurrency, and runtime overhead.

Model identity

Base model
Qwen/Qwen3.6-35B-A3B
Updated
5 months ago
HuggingFace revision
a483e9e6cb

Popularity and trust

Downloads (last month)

1.2M

Likes

1.7K

Spaces using this model

13

Files and formats

Weight formats

GGUF

Repository files

31

Chat template

Not detected

GPU deployment scenarios

Estimated from parameter count and quantisation. Will switch to “Verified by Badgr” once a real run backs a tier.

Testing

A100 80GB

Short context, low concurrency

Small production

H100 80GB

8K context, 1-4 concurrent requests

Higher throughput

H200 141GB

32K context, continuous batching

Large production

A100 80GB

Higher concurrency

Estimated — multimodal inputs, long context, and concurrency all increase real VRAM use beyond this estimate.

Also runs well on H100 80GB, H200 141GB. Available in United States, Europe, Asia Pacific.

Serving compatibility

RuntimeStatusNotes
vLLMEstimatedUsed for Badgr dedicated endpoints
TransformersDeclared by sourceBasic fallback
llama.cppVerified by BadgrConfirmed by a real badgr serve run (deployment dep-03c936ee8b)
SGLangUnknownNot evaluated
OllamaVerified by BadgrConfirmed by a real badgr serve run (deployment dep-ab1f15ad47)
DiffusersUnknownNot evaluated
PyTorchUnknownNot evaluated
TensorRT-LLMUnknownConversion may be required
TGIUnknownNot evaluated

Ready-to-run Badgr configurations

Quick test

badgr serve unsloth/Qwen3.6-35B-A3B-GGUF --max-cost 2

Validated dedicated endpoint command

badgr serve unsloth/Qwen3.6-35B-A3B-GGUF --gpu A100 80GB --max-cost 10

Advanced configuration (defaults to automatic)

  • Runtime
  • Quantisation
  • GPU and GPU count
  • Context length
  • Maximum concurrency
  • Region
  • Maximum hourly spend
  • Persistent or capped runtime

Estimated pricing

Provider estimate: cold start

3–8 min

Provider estimate: endpoint cost

$1.40 – $1.40/hr

Idle cost

$0 when stopped

Per-token throughput cost is not shown here: Badgr has not benchmarked this model yet, and this page does not display figures it cannot back with real data.

Recommended Badgr routes

A100 80GB · Europe

Estimated

starting from $1.40/hr

Badgr estimated starting price

Best for

LoRA Training, vLLM Endpoint, Qwen 2.5 32B Instruct

Startup: 3–8 min

Reliability: Good

Last checked: Live marketplace price not available yet

A100 80GB · Europe

Estimated

starting from $1.40/hr

Badgr estimated starting price

Best for

LoRA Training, vLLM Endpoint, Qwen 2.5 32B Instruct

Startup: 3–8 min

Reliability: High

Last checked: Live marketplace price not available yet

A100 80GB · Europe

Estimated

starting from $1.40/hr

Badgr estimated starting price

Best for

LoRA Training, vLLM Endpoint, Qwen 2.5 32B Instruct

Startup: 3–8 min

Reliability: High

Last checked: Live marketplace price not available yet

A100 80GB · Europe

Estimated

starting from $1.40/hr

Badgr estimated starting price

Best for

LoRA Training, vLLM Endpoint, Qwen 2.5 32B Instruct

Startup: 3–8 min

Reliability: Good

Last checked: Live marketplace price not available yet

A100 80GB · Europe

Estimated

starting from $1.40/hr

Badgr estimated starting price

Best for

LoRA Training, vLLM Endpoint, Qwen 2.5 32B Instruct

Startup: 3–8 min

Reliability: High

Last checked: Live marketplace price not available yet

A100 80GB · Asia Pacific

Estimated

starting from $1.40/hr

Badgr estimated starting price

Best for

LoRA Training, vLLM Endpoint, Qwen 2.5 32B Instruct

Startup: 3–8 min

Reliability: High

Last checked: Live marketplace price not available yet

Known limitations

  • Memory use increases with context length and concurrency.

Related troubleshooting