TII
Falcon 40B Instruct
Legacy22.4KDownloads1.2KLikesMay 2023Veröffentlicht8K TokenKontextApache 2.0Lizenz50 GutQualität
Falcon 40B Instruct (40B parameters) requires approximately 32.4 GB of VRAM with Q5_K_M quantization. For the best balance of quality and speed, we recommend hardware with at least 38 GB of VRAM.
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— kopieren & einfügen, um lokal auszuführenCopy-paste commands to run Falcon 40B Instruct on your machine.
Run
docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
--hf-repo "tiiuae/falcon-40b-instruct" \
--hf-file "falcon-40b-instruct-Q5_K_M.gguf" \
-c 4096 -ngl 99Quick specs
Parameters40B
Architecturedense
Context8K tokens
Modalitytext
Min RAM15.6 GB
Rec. RAM28.8 GB (Q5_K_M)
LicenseApache 2.0
FamilyFalcon
✓ Chat✓ Reasoning
About this model
- •You are looking for a ready-to-use chat/instruct model based on Falcon-40B
- •Falcon-40B is the best open-source model available.: It outperforms LLaMA, StableLM, RedPajama, MPT, etc. See the OpenLLM Leaderboard
- •It features an architecture optimized for inference: , with FlashAttention (Dao et al., 2022) and multiquery (Shazeer et al., 2019)
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Quantisierungsoptionen
VRAM-Schätzungen nach Quantisierungsstufe
No hardware detected — fit column shows raw VRAM estimates
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 15.6 GB | Low | — |
Q3_K_S | 3 | 19.6 GB | Low | — |
NVFP4 | 4 | 22.4 GB | Medium | — |
Q4_K_M | 4 | 24.4 GB | Medium | — |
Q5_K_M | 5 | 28.8 GB | High | — |
Q6_K | 6 | 32.8 GB | High | — |
Q8_0 | 8 | 42.8 GB | Very High | — |
F16 | 16 | 82.0 GB | Maximum | — |
Quality benchmarks
Falcon 40B Instruct benchmark scores
Reasoning
MMLU-Pro14.0%
GPQA Diamond—
MATH-5002.0%
ARC Challenge—
General
Chatbot Arena—
IFEval24.5%
Source: community · 2025-01-01
Hardware-Kompatibilität
Eignungsschätzungen für alle Hardware
Computing compatibility...
Speicheraufschlüsselung
Reference: RTX 2060 6GB
Weights28.8 GB
KV Cache1.8 GB
Runtime1.2 GB
Headroom0.6 GB
Häufig gestellte Fragen
FAQ — Falcon 40B Instruct
Siehe auch