InternScience · Released Oct 15, 2026 · observed 26 Oct 2026
Public-source support evidence
We ran the Q4_K_M GGUF on one Mac; see Hardware notes below. Community MLX weights are available; the architecture is listed in llama.cpp and vLLM.
InternScience/Sage-A1.5
Sage-A1.5 is a text generation model published by InternScience 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 ↗A current public MLX upload with an exact base_model match was observed. Upload availability only; this model was not loaded or hardware-tested.
Checked 2026-10-27 00:08 UTC
Evidence 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 28 GB is the recommended Q4_K_M quant (21.7 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?
Q4_K_M · 21.7 GB observed · about 28 GB ↗About 28 GB using file size × 1.2 + 1.5 GB. Fit is an estimate; compatibility, speed, context length and hardware have not been tested.
Which file should I grab?
Q4_K_M · 21.7 GB observed · about 28 GB ↗About 28 GB using file size × 1.2 + 1.5 GB. Fit is an estimate; compatibility, speed, context length and hardware have not been tested.
Which file should I grab?
Q4_K_M · 21.7 GB observed · about 28 GB ↗About 28 GB using file size × 1.2 + 1.5 GB. Fit is an estimate; compatibility, speed, context length and hardware have not been tested.
Which file should I grab?
Q4_K_M · 21.7 GB observed · about 28 GB ↗About 28 GB using file size × 1.2 + 1.5 GB. Fit is an estimate; compatibility, speed, context length and hardware have not been tested.
Which file should I grab?
Q4_K_M · 21.7 GB observed · about 28 GB ↗About 28 GB using file size × 1.2 + 1.5 GB. Fit is an estimate; compatibility, speed, context length and hardware have not been tested.
Which file should I grab?
Q4_K_M · 21.7 GB observed · about 28 GB ↗About 28 GB using file size × 1.2 + 1.5 GB. Fit is an estimate; compatibility, speed, context length and hardware have not been tested.
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.
| Uploader | Format & quant | Observed size | Estimated fit | Files |
|---|---|---|---|---|
| InternScienceInternScience/Sage-A1.5-Q4_K_M-GGUF ↗Observed 27 Oct 2026 | GGUF · Q4_K_M | 21.7 GB | 32 GB, 64 GB, 128 GB, 192 GB, 256 GB, 512 GBEstimate only; requires the complete GGUF quant group. | 1 file
|
| mlx-communitymlx-community/Sage-A1.5-OptiQ-4bit ↗Observed 27 Oct 2026 | MLX · Quant unknown | Size unknown | UnknownUnknown: completeness or a complete GGUF quant group was not verified. | 7 files |
CURATED TRACKING
No curated issues verified for this snapshot. An empty list does not mean there are no bugs.
HARDWARE NOTES
We ran the Q4_K_M GGUF (21.71 GB, InternScience/Sage-A1.5-Q4_K_M-GGUF) on an Apple M4 Max Mac, 128 GiB unified memory, macOS 27.0.1, Metal with llama.cpp b11912 (upstream, 961c376) on 26 Oct 2026.
Decode: 104.9 tok/s on a short prompt, 102.9 tok/s on a long prompt (medians of 3 runs).
Peak memory: 21.0 GiB (llama-server footprint).
llama-bench: pp512 1,630.8 tok/s, tg128 107.2 tok/s.
Answer checks: 4 of 4 prompts passed (quick pass/fail sanity checks, not a quality benchmark).
Text only: the vision projector (mmproj) file was not loaded, so image input was not tested.
Thinking off (enable_thinking=false).
One machine, one run set: temperature 0, 8K context, 1 warm-up plus 3 runs per prompt. Short prompt is 23 tokens; long prompt is 1,431 tokens (each model counts with its own tokenizer). Weights were loaded from an external USB drive with mmap off; load time is not published for this run. Your speed will differ with hardware, context length and settings.
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