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authorPaul Buetow <paul@buetow.org>2026-03-18 18:52:31 +0200
committerPaul Buetow <paul@buetow.org>2026-03-18 18:52:31 +0200
commit98858030d4c9c81849dcd49d6212255cbda28755 (patch)
tree32ba6ce9f519ca1bca9b499d62407d7489b1a957 /snippets/hyperstack
parent3fe076087ea50ca56f211c4f4c00c8c08b0479da (diff)
gpt-oss-120b: raise max_model_len to 131072
MXFP4 KV cache is compact enough that vLLM allocated 168K token blocks (10560×16) at 0.92 utilization — the 40K limit was too conservative and caused negative max_tokens errors in long Claude Code sessions. Co-Authored-By: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com>
Diffstat (limited to 'snippets/hyperstack')
-rw-r--r--snippets/hyperstack/hyperstack-vm.toml6
1 files changed, 3 insertions, 3 deletions
diff --git a/snippets/hyperstack/hyperstack-vm.toml b/snippets/hyperstack/hyperstack-vm.toml
index e8f6251..d7d09e3 100644
--- a/snippets/hyperstack/hyperstack-vm.toml
+++ b/snippets/hyperstack/hyperstack-vm.toml
@@ -123,13 +123,13 @@ tensor_parallel_size = 1
tool_call_parser = ""
# OpenAI GPT-OSS 120B — powerful MoE (5.1B active / 117B total, MXFP4), ~65 GB on A100.
-# Leaves ~8 GB for KV cache; 40K context is the practical ceiling on a single A100 80GB.
-# Set >= 40K so Claude Code's ~33K system prompt fits (opencode needs only ~14K).
+# MXFP4 KV cache is very compact: vLLM allocates 168K token blocks (10560×16) at 0.92 util.
+# 131072 fits Claude Code's ~33K system prompt with room for long conversations.
# tool_call_parser = "" disables --enable-auto-tool-choice (same reason as gpt-oss-20b).
[vllm.presets.gpt-oss-120b]
model = "openai/gpt-oss-120b"
container_name = "vllm_gpt_oss_120b"
-max_model_len = 40960
+max_model_len = 131072
gpu_memory_utilization = 0.92
tensor_parallel_size = 1
tool_call_parser = ""