TheDrummer
Cydonia 24B v4.3
Top-of-line 24B roleplay model, Mistral-Small-3.2-24B base. Active development cycle — TheDrummer ships frequent revisions tracking the latest base models.
Check Your Hardware
See which quantizations of Cydonia 24B v4.3 your hardware can run.
Quantization Options
| Quantization | Bits | File Size | VRAM Needed | RAM Needed | Quality |
|---|---|---|---|---|---|
| BF16 | 16 | 48 GB | 48.5 GB | 49 GB | 100% |
| Q4_K_M | 4.5 | 14.4 GB | 14.9 GB | 15.4 GB | 85% |
Context window & KV cache
Adds 1.50 GB to VRAMLong chats and RAG inputs cost real memory. Drag to see how 32K vs 128K context shifts your grade.
Model native max: 32K tokens. KV-cache estimate is approximate (±30 %); real usage depends on attention layout.
How to run Cydonia 24B v4.3
Pick a runtime — copy & paste. Commands are pre-filled with this model’s repo.
GUI. Browse → download → chat. MLX on Apple Silicon.
LM Studio home →- 1
Open LM Studio
Go to the 🔍 Search tab.
- 2
Search for
mradermacher/Cydonia-24B-v4.3-GGUF - 3
Download
Pick the Q4_K_M quant — best balance of size vs. quality.
- 4
Chat
Hit ▶ Load Model and start chatting. Toggle 'Local Server' to expose an OpenAI-compatible API on :1234.
Community benchmarks
Real tokens/sec reports from people running Cydonia 24B v4.3 on actual hardware.
No community runs yet for this model. Be the first to submit your numbers.
Self-host serving plan
Want to host Cydonia 24B v4.3for many users? Or run it on a card that’s technically too small? Slide the knobs.
VRAM needed
16.6 GB
14.9 GB weights + 1.2 GB KV
Aggregate tok/s
10
across 1 user
Per-user tok/s
10
24 B dense
✅ Fits in 24 GB VRAM with 7.4 GB headroom. Pure-GPU inference — full speed.
Throughput is a sub-linear estimate: doubling users adds ~70 % of single-user TPS until ~8, then plateaus on memory bandwidth. MoE models scale concurrency much better because each user activates a different subset of experts.
See It In Action
Real model outputs generated via RunThisModel.com — watch responses stream in real time.
Outputs generated by real AI models via RunThisModel.com. Generation speed shown is from cloud inference. Local speeds vary by hardware — check your device.
Frequently Asked Questions
How much VRAM do I need to run Cydonia 24B v4.3?
Cydonia 24B v4.3 requires 14.9GB VRAM minimum with BF16 quantization. For full precision, you need 48.5GB VRAM.
What is the best quantization for Cydonia 24B v4.3?
Q4_K_M offers the best balance of quality and VRAM usage. Q8_0 is near-lossless if you have enough VRAM.