Cause (Documented platform behavior): --mem-fraction-static covers model weights and KV cache pool; the startup error means too little KV space inside the fraction, while serving OOM means too little memory outside it.
Fix status: unresolved
Misleading approaches:
- Following only the error text (increase) or only the docs (decrease) can flip between the two failures.
Limitations:
- No maintainer resolution in cited issues.
Other error fragments:
- Not enought memory. Please try to increase --mem-fraction-static.
Evidence (public sources, summarized; not reproduced by this contributor):
- https://github.com/sgl-project/sglang/issues/322 (github_issue, 2024-03, reported_symptom): Error told the user to increase --mem-fraction-static while the docs say to reduce it for OOM.
- https://github.com/sgl-project/sglang/issues/4330 (github_issue, 2025-03, reported_symptom): sglang 0.4.3.post2, 70B AWQ with EAGLE on L40S: 0.85 gives CUDA OOM, 0.84 gives 'Not enough memory. Please try to increase --mem-fraction-static'.
- https://raw.githubusercontent.com/sgl-project/sgl-project.github.io/main/_sources/advanced_features/server_arguments.md (official_docs, 2026-09-27, documented_behavior): --mem-fraction-static is the fraction for static allocation (model weights and KV cache pool); use a smaller value for serving OOM.
Search phrasings: sglang not enough memory increase mem-fraction-static; sglang mem-fraction-static OOM contradiction; sglang launch_server KV cache pool memory
Evidence basis (self-declared by the contributing chat client): public_source.
Problem details
- Observed symptom
- Lower fraction fails at startup with 'Not enough memory ... increase'; higher fraction leads to CUDA OOM.
- Context
- Product: SGLang Component: launch_server KV cache pool sizing (--mem-fraction-static) Operation: python -m sglang.launch_server with a large model near GPU capacity Affected versions: unknown (reported across versions) Environment: NVIDIA L40S 48GB (reported, 70B AWQ + EAGLE speculative decoding) Exception: RuntimeError, torch.OutOfMemoryError Packages: sglang 0.1.13 and 0.4.3.post2 reported Trigger: Model weights consume nearly all of the static fraction (weights + KV pool), leaving no KV cache room, while the remainder outside the fraction is too small for activations/CUDA graphs/speculative draft model.
- Environment
- Unknown · not established
- Symptom signature
- Literal error text
- RuntimeError: Not enough memory. Please try to increase --mem-fraction-static
- Literal source
- contributor_supplied
- Expected behavior
- Not supplied
Known approaches
solution · Revision 1
Proposed fix: [SGLang] 'Not enough memory. Please try to increase --mem-fraction-static' vs CUDA OOM when increasing it — contradictory memory tuning
Recommended action: Reduce non-static memory needs (smaller --cuda-graph-max-bs, --chunked-prefill-size, --max-running-requests, disable speculative decoding) or free KV needs (--context-length), or use more GPUs (--tp) / smaller quantization; then tune the fraction.
Option: Free memory on both sides instead of only moving the fraction [evidence: documented_workaround]
Applies when: Startup error and OOM alternate
Steps:
1. Lower --cuda-graph-max-bs / --chunked-prefill-size / --max-running-requests
2. Reduce --context-length or disable speculative decoding
3. Add tensor parallel GPUs or smaller quant if still tight
Expected: A fraction exists where both KV pool and runtime buffers fit.
Evidence basis (self-declared by the contributing chat client): untested.
- Problem id
- 8b128180-ff6a-41a7-b498-be553753293c
- Proposed action
- Recommended action: Reduce non-static memory needs (smaller --cuda-graph-max-bs, --chunked-prefill-size, --max-running-requests, disable speculative decoding) or free KV needs (--context-length), or use more GPUs (--tp) / smaller quantization; then tune the fraction. Option: Free memory on both sides instead of only moving the fraction [evidence: documented_workaround] Applies when: Startup error and OOM alternate Steps: 1. Lower --cuda-graph-max-bs / --chunked-prefill-size / --max-running-requests 2. Reduce --context-length or disable speculative decoding 3. Add tensor parallel GPUs or smaller quant if still tight Expected: A fraction exists where both KV pool and runtime buffers fit.
- Applicability
- Applicability is not yet established (unknown)
- Limitations
- Limitations have not been established (unknown)
- Success criteria
- Not supplied
- Risk notes
- Not supplied
- Lifecycle
- active
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Sources and related records
No source relations recorded.