reflection · Released Oct 7, 2026 · observed 26 Oct 2026
Public-source support evidence
Exact checkpoint execution is unverified. The architecture is listed in llama.cpp and vLLM.
reflection/Beam-1.0-501B-A23B
Beam-1.0-501B-A23B is a text generation model published by reflection on Hugging Face. We have not written a summary yet; see the model card ↗.
View source model ↗SUPPORT EVIDENCE
The model config architecture is listed in this runtime registry. This is family/architecture evidence only; exact checkpoint loading, model-specific configuration, hardware, and generation were not tested.
Checked 2026-10-27 00:08 UTC
Evidence source ↗The exact model and runtime-specific sources were checked; no positive model-level evidence was established.
Checked 2026-10-26 23:48 UTC
Version v0.40.11
Checked source ↗The exact model and runtime-specific sources were checked; no positive model-level evidence was established.
Checked 2026-10-27 00:28 UTC
Checked source ↗Checked the exact model config and the runtime architecture registry; no matching declared architecture was found. This is unknown, not evidence of incompatibility.
Checked 2026-10-27 00:08 UTC
Checked source ↗The model config architecture is listed in this runtime registry. This is family/architecture evidence only; exact checkpoint loading, model-specific configuration, hardware, and generation were not tested.
Checked 2026-10-27 00:08 UTC
Evidence source ↗MLX community uploads may target mlx-vlm; an upload observation does not establish mlx-lm compatibility.
MEMORY ESTIMATES
The summary estimate of about 379 GB is the recommended Q4_K_M quant (314.5 GB observed), from file size × 1.2 + 1.5 GB. Each card is the largest observed quant whose estimate fits that capacity.
Which file should I grab?
doesn't fitNo observed complete quant fits this capacity using file size × 1.2 + 1.5 GB.
Which file should I grab?
doesn't fitNo observed complete quant fits this capacity using file size × 1.2 + 1.5 GB.
Which file should I grab?
doesn't fitNo observed complete quant fits this capacity using file size × 1.2 + 1.5 GB.
Which file should I grab?
doesn't fitNo observed complete quant fits this capacity using file size × 1.2 + 1.5 GB.
Which file should I grab?
UD-IQ1_S · 103.1 GB observed · about 126 GB ↗About 126 GB using file size × 1.2 + 1.5 GB. Fit is an estimate; compatibility, speed, context length and hardware have not been tested. Link points to shard 1; all 4 linked shards are required.
Which file should I grab?
IQ2_XS · 151.7 GB observed · about 184 GB ↗About 184 GB using file size × 1.2 + 1.5 GB. Fit is an estimate; compatibility, speed, context length and hardware have not been tested. Link points to shard 1; all 4 linked shards are required.
Which file should I grab?
IQ3_XXS · 211.1 GB observed · about 255 GB ↗About 255 GB using file size × 1.2 + 1.5 GB. Fit is an estimate; compatibility, speed, context length and hardware have not been tested. Link points to shard 1; all 6 linked shards are required.
Which file should I grab?
Q6_K_S · 420.6 GB observed · about 507 GB ↗About 507 GB using file size × 1.2 + 1.5 GB. Fit is an estimate; compatibility, speed, context length and hardware have not been tested. Link points to shard 1; all 11 linked shards are required.
Memory estimates are the observed file size plus fixed headroom (20% plus 1.5 GB runtime allowance); real needs also depend on context length, KV cache and runtime settings. Fit is an estimate; it does not establish runtime compatibility, speed, context length, or hardware performance. Text-weights-only estimates do not include a projector or total vision memory where unknown.
Terms: a quant is a lower-precision version of the weights; GGUF is a file format used by llama.cpp and compatible apps; MLX targets Apple silicon; vLLM is a model-serving engine for NVIDIA GPUs; the KV cache is stored attention state that grows with context length. Terms explained ↗
OBSERVED FILES
Sizes and file groups come from the listed uploader repositories. A size is marked as an estimated fit only for a complete observed GGUF quant group.
CURATED TRACKING
No curated issues verified for this snapshot. An empty list does not mean there are no bugs.
HARDWARE NOTES
No execution or benchmark results are published for this model yet.
COMPARE
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EMBED
Works in GitHub READMEs and Hugging Face model cards. The badge updates when the site rebuilds.