Qwen · Qwen3
Qwen3 30B A3B Instruct 2507
Verified by Badgr · ServeQwen3 30B A3B Instruct 2507 is a 30.5B chat and text-generation model available through supported Badgr execution routes.
Last validated or meaningfully updated: 2026-10-10
✓ Verified by Badgr · vLLM · Serve
Last verified 2026-10-10
badgr serve Qwen/Qwen3-30B-A3B-Instruct-2507 --max-cost 3 --startup-timeout 40- GPU
- NVIDIA H100 80GB HBM3Reported by the provider, not confirmed inside the container
- Time to verified
- 201s
- Deployment
- dep-e02bfd5e45
- ✓ vLLM started
- ✓ 1-token /v1/completions request returned HTTP 200
- ✓ final_state = VERIFIED
- ✓ teardown completed
About 61 GB of bf16 weights, so Badgr's VRAM floor (75 GB) sent it straight to an H100 80GB. Before that floor applied to named GPUs, an earlier launch of this model was placed on a 48 GB card first and ran out of memory.
Raw evidence
final_state=VERIFIED failure_class=None providers_tried=1/1 teardown_confirmed=False spend_usd=0.1821
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
- Qwen3MoeForCausalLM
- Licence
- Apache-2.0
- Minimum VRAM
- ~65GB
- Context
- 256K tokens
Recommended: A100 80GB. VRAM is an estimate and increases with context, cache, concurrency, and runtime overhead.
Model identity
- Updated
- 1 years ago
- HuggingFace revision
- 0d7cf23991
Popularity and trust
Downloads (last month)
967.0K
Likes
841
Spaces using this model
88
Files and formats
Weight formats
Safetensors
Repository files
27
Tokenizer
BPE
Chat template
Available
GPU deployment scenarios
Estimated from parameter count and quantisation. This model's one verified real run was reported by the provider as NVIDIA H100 80GB HBM3, which isn't one of the tiers below.
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
| Runtime | Status | Notes |
|---|---|---|
| vLLM | Verified by Badgr | Confirmed by a real badgr serve run (deployment dep-e02bfd5e45) |
| Transformers | Declared by source | Basic fallback |
| llama.cpp | Requires GGUF conversion | No GGUF weights found in repo |
| SGLang | Unknown | Not evaluated |
| Ollama | Unknown | Not evaluated |
| Diffusers | Unknown | Not evaluated |
| PyTorch | Unknown | Not evaluated |
| TensorRT-LLM | Unknown | Conversion may be required |
| TGI | Unknown | Not evaluated |
Ready-to-run Badgr configurations
Quick test
badgr serve Qwen/Qwen3-30B-A3B-Instruct-2507 --max-cost 2Validated dedicated endpoint command
badgr serve Qwen/Qwen3-30B-A3B-Instruct-2507 --gpu A100 80GB --max-cost 10Advanced 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
$1.30 – $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 · United States
Availablefrom $1.30/hr
Best for
LoRA Training, vLLM Endpoint, Qwen 2.5 32B Instruct
Startup: 3–8 min
Reliability: High
Last checked: just now
A100 80GB · United States
Estimatedstarting 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
Estimatedstarting 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
Estimatedstarting 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
Estimatedstarting 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
Estimatedstarting 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
Known limitations
- Memory use increases with context length and concurrency.