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2aeafb4
add dsv4 1k1k
hshrivastava-droid Jun 9, 2026
984a91e
update configs
hshrivastava-droid Jun 9, 2026
7c91283
split configs
hshrivastava-droid Jun 10, 2026
47460ef
update runner
hshrivastava-droid Jun 11, 2026
71ac4b8
Merge branch 'main' into nv/dsv4-gb300-v2
hshrivastava-droid Jun 11, 2026
fd84ba5
Update perf-changelog.yaml
hshrivastava-droid Jun 11, 2026
37100c4
Update nvidia-master.yaml
Oseltamivir Jun 11, 2026
ae2385e
update container
hshrivastava-droid Jun 15, 2026
74145a9
Merge branch 'main' into nv/dsv4-gb300-v2
hshrivastava-droid Jun 15, 2026
9e81ea9
Update perf-changelog.yaml
hshrivastava-droid Jun 15, 2026
a87852e
update image to latest
hshrivastava-droid Jun 16, 2026
a0e8fc2
add image change
hshrivastava-droid Jun 16, 2026
7680f41
Merge branch 'main' into nv/dsv4-gb300-v2
hshrivastava-droid Jun 16, 2026
1fa0642
update nv elif
hshrivastava-droid Jun 16, 2026
f11e4e6
Merge branch 'main' into nv/dsv4-gb300-v2
hshrivastava-droid Jun 16, 2026
30fe6f2
update cluster to nv
hshrivastava-droid Jun 16, 2026
f83ea43
update model name
hshrivastava-droid Jun 16, 2026
e48f6b3
Merge remote-tracking branch 'origin/nv/dsv4-gb300-v2' into nv/dsv4-g…
hshrivastava-droid Jun 16, 2026
d873c19
Merge branch 'main' into nv/dsv4-gb300-v2
hshrivastava-droid Jun 16, 2026
395f577
image update to stable
hshrivastava-droid Jun 17, 2026
90cee64
Merge branch 'main' into nv/dsv4-gb300-v2
hshrivastava-droid Jun 17, 2026
bff6056
Consolidate dsv4-fp4-gb300-dynamo-sglang-mtp: merge 1k1k scenarios in…
hshrivastava-droid Jul 2, 2026
656ffbf
Revert non-MTP 8k1k recipe container bumps
hshrivastava-droid Jul 2, 2026
da5295d
Merge branch 'main' into nv/dsv4-gb300-v2
hshrivastava-droid Jul 2, 2026
d2854ce
Bump dsv4-fp4-gb300-dynamo-sglang-mtp image to latest nightly
hshrivastava-droid Jul 6, 2026
622eeb1
Merge remote-tracking branch 'origin/main' into nv/dsv4-gb300-v2
hshrivastava-droid Jul 6, 2026
59f4a24
Bump dsv4-fp4-gb300-dynamo-sglang-mtp image to sglang 0710 nightly
hshrivastava-droid Jul 10, 2026
1300a1c
Pin srt-slurm to v1.0.17 for dsv4-fp4-gb300-dynamo-sglang-mtp
hshrivastava-droid Jul 10, 2026
55a5754
merge: sync main into dsv4 GB300 config branch
hshrivastava-droid Jul 10, 2026
46798d2
update dynamo version
hshrivastava-droid Jul 16, 2026
6d4c42c
Merge branch 'main' into nv/dsv4-gb300-v2
hshrivastava-droid Jul 16, 2026
4d0d2bb
Merge branch 'main' into nv/dsv4-gb300-v2
hshrivastava-droid Jul 20, 2026
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Original file line number Diff line number Diff line change
@@ -0,0 +1,156 @@
name: "dsv4-pro-gb300-disagg-1k1k-mtp-1p1d-dep16-conc8192"

sbatch_directives:
cpus-per-task: '144'
mem: '0'

dynamo:
version: 1.2.1

frontend:
type: dynamo
enable_multiple_frontends: true
num_additional_frontends: 8

model:
path: deepseek-v4-pro
container: "lmsysorg/sglang:nightly-dev-cu13-20260710-cfc66e05"
precision: fp4

resources:
gpu_type: gb300
gpus_per_node: 4
prefill_nodes: 1
prefill_workers: 1
gpus_per_prefill: 4
decode_nodes: 4
decode_workers: 1
gpus_per_decode: 16

backend:
type: sglang

prefill_environment:
PYTHONUNBUFFERED: '1'
SGLANG_RADIX_DISABLE_REUSE: '1'
SGLANG_JIT_DEEPGEMM_FAST_WARMUP: '1'
SGLANG_DEFAULT_THINKING: '1'
SGLANG_DSV4_REASONING_EFFORT: max
SGLANG_OPT_SWA_SPLIT_LEAF_ON_INSERT: '1'
SGLANG_OPT_USE_JIT_NORM: '1'
SGLANG_OPT_USE_JIT_INDEXER_METADATA: '1'
SGLANG_OPT_USE_TOPK_V2: '1'

SGLANG_OPT_SWA_EVICT_DROP_PAGE_MARGIN: '1'
SGLANG_OPT_USE_CUSTOM_ALL_REDUCE_V2: '1'
SGLANG_OPT_USE_FAST_MASK_EP: '1'
SGLANG_OPT_USE_DEEPGEMM_MEGA_MOE: '1'
SGLANG_OPT_FIX_HASH_MEGA_MOE: '1'
SGLANG_OPT_DEEPGEMM_MEGA_MOE_NUM_MAX_TOKENS_PER_RANK: '9216'
SGLANG_OPT_FIX_MEGA_MOE_MEMORY: '1'
SGLANG_OPT_FIX_NEXTN_MEGA_MOE: '1'
SGLANG_DEEPEP_NUM_MAX_DISPATCH_TOKENS_PER_RANK: '0'

NCCL_MNNVL_ENABLE: '1'
NCCL_CUMEM_ENABLE: '1'
SGLANG_MOONCAKE_CUSTOM_MEM_POOL: 'True'
MC_FORCE_MNNVL: '1'
SGLANG_DISAGGREGATION_BOOTSTRAP_TIMEOUT: '100000'
SGLANG_DISAGGREGATION_WAITING_TIMEOUT: '100000'
SGLANG_OPT_SWA_RELEASE_LEAF_LOCK_AFTER_WINDOW: '1'

decode_environment:
PYTHONUNBUFFERED: '1'
SGLANG_RADIX_DISABLE_REUSE: '1'
SGLANG_JIT_DEEPGEMM_FAST_WARMUP: '1'
SGLANG_DEFAULT_THINKING: '1'
SGLANG_DSV4_REASONING_EFFORT: max
SGLANG_OPT_SWA_SPLIT_LEAF_ON_INSERT: '1'
SGLANG_OPT_USE_JIT_NORM: '1'
SGLANG_OPT_USE_JIT_INDEXER_METADATA: '1'
SGLANG_OPT_USE_TOPK_V2: '1'

SGLANG_OPT_SWA_EVICT_DROP_PAGE_MARGIN: '1'
SGLANG_OPT_USE_FAST_MASK_EP: '1'
SGLANG_OPT_USE_DEEPGEMM_MEGA_MOE: '1'
SGLANG_OPT_FIX_HASH_MEGA_MOE: '1'
SGLANG_OPT_DEEPGEMM_MEGA_MOE_NUM_MAX_TOKENS_PER_RANK: '4096'
SGLANG_OPT_FIX_MEGA_MOE_MEMORY: '1'
SGLANG_OPT_FIX_NEXTN_MEGA_MOE: '1'
SGLANG_DEEPEP_NUM_MAX_DISPATCH_TOKENS_PER_RANK: '0'

NCCL_MNNVL_ENABLE: '1'
NCCL_CUMEM_ENABLE: '1'
SGLANG_MOONCAKE_CUSTOM_MEM_POOL: 'True'
MC_FORCE_MNNVL: '1'
SGLANG_DISAGGREGATION_BOOTSTRAP_TIMEOUT: '100000'
SGLANG_DISAGGREGATION_WAITING_TIMEOUT: '100000'
SGLANG_OPT_SWA_RELEASE_LEAF_LOCK_AFTER_WINDOW: '1'
SGLANG_OPT_USE_CUSTOM_ALL_REDUCE_V2: "0" # CAR_V2 is single-node only.

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Missing distributed timeout dep16

Medium Severity

disagg-1p1d-dep8-conc8192-mtp.yaml sets TORCH_DISTRIBUTED_DEFAULT_TIMEOUT to 1800 in decode_environment for multi-node decode, but the new dep16 recipes (four decode nodes, TP16) omit it. Longer multi-node decode init can hit the default shorter timeout.

Additional Locations (1)
Fix in Cursor Fix in Web

Reviewed by Cursor Bugbot for commit 37100c4. Configure here.


sglang_config:
prefill:
served-model-name: deepseek-ai/DeepSeek-V4-Pro
model-path: "/model/"
trust-remote-code: true
tool-call-parser: deepseekv4

disaggregation-mode: prefill
disaggregation-transfer-backend: mooncake

tensor-parallel-size: 4
data-parallel-size: 4
expert-parallel-size: 4

enable-dp-attention: true
enable-dp-lm-head: true

moe-a2a-backend: deepep
deepep-config: '{"normal_dispatch":{"num_sms":96},"normal_combine":{"num_sms":96}}'

mem-fraction-static: 0.9
max-running-requests: 1024
cuda-graph-max-bs: 1024
chunked-prefill-size: 32768
stream-interval: 60

decode:
served-model-name: deepseek-ai/DeepSeek-V4-Pro
model-path: "/model/"
trust-remote-code: true
tool-call-parser: deepseekv4

disaggregation-mode: decode
disaggregation-transfer-backend: mooncake

tensor-parallel-size: 16
data-parallel-size: 16
expert-parallel-size: 16

enable-dp-attention: true
enable-dp-lm-head: true

moe-a2a-backend: deepep
deepep-config: '{"normal_dispatch":{"num_sms":96},"normal_combine":{"num_sms":96}}'

speculative-algo: "EAGLE"
speculative-num-steps: 3
speculative-eagle-topk: 1
speculative-num-draft-tokens: 4

mem-fraction-static: 0.9
max-running-requests: 18432
cuda-graph-max-bs: 1024
swa-full-tokens-ratio: 0.15
context-length: 16384
stream-interval: 60

benchmark:
type: "sa-bench"
isl: 1024
osl: 1024
random_range_ratio: 0.8
concurrencies: "8192"
req_rate: "inf"
use_chat_template: true
custom_tokenizer: "sa_bench_tokenizers.sglang_deepseek_v4.SGLangDeepseekV4Tokenizer"
Original file line number Diff line number Diff line change
@@ -0,0 +1,157 @@
name: "dsv4-pro-gb300-disagg-1k1k-mtp-1p1d-dep8-conc8192"

sbatch_directives:
cpus-per-task: '144'
mem: '0'

dynamo:
version: 1.2.1

frontend:
type: dynamo
enable_multiple_frontends: true
num_additional_frontends: 8

model:
path: deepseek-v4-pro
container: "lmsysorg/sglang:nightly-dev-cu13-20260710-cfc66e05"
precision: fp4

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High-conc precision mismatch

Medium Severity

The three high-throughput 1k1k MTP recipes declare model.precision as fp4, but the established GB300 DeepSeek-V4 SGLang MTP overlays use mxfp4 for the same hardware and container family. That mismatch can steer the runner toward the wrong quantization or weight layout for GB300 FP4 serving.

Additional Locations (1)
Fix in Cursor Fix in Web

Reviewed by Cursor Bugbot for commit 7680f41. Configure here.


resources:
gpu_type: gb300
gpus_per_node: 4
prefill_nodes: 1
prefill_workers: 1
gpus_per_prefill: 4
decode_nodes: 2
decode_workers: 1
gpus_per_decode: 8

backend:
type: sglang

prefill_environment:
PYTHONUNBUFFERED: '1'
SGLANG_RADIX_DISABLE_REUSE: '1'
SGLANG_JIT_DEEPGEMM_FAST_WARMUP: '1'
SGLANG_DEFAULT_THINKING: '1'
SGLANG_DSV4_REASONING_EFFORT: max
SGLANG_OPT_SWA_SPLIT_LEAF_ON_INSERT: '1'
SGLANG_OPT_USE_JIT_NORM: '1'
SGLANG_OPT_USE_JIT_INDEXER_METADATA: '1'
SGLANG_OPT_USE_TOPK_V2: '1'

SGLANG_OPT_SWA_EVICT_DROP_PAGE_MARGIN: '1'
SGLANG_OPT_USE_CUSTOM_ALL_REDUCE_V2: '1'
SGLANG_OPT_USE_FAST_MASK_EP: '1'
SGLANG_OPT_USE_DEEPGEMM_MEGA_MOE: '1'
SGLANG_OPT_FIX_HASH_MEGA_MOE: '1'
SGLANG_OPT_DEEPGEMM_MEGA_MOE_NUM_MAX_TOKENS_PER_RANK: '9216'
SGLANG_OPT_FIX_MEGA_MOE_MEMORY: '1'
SGLANG_OPT_FIX_NEXTN_MEGA_MOE: '1'
SGLANG_DEEPEP_NUM_MAX_DISPATCH_TOKENS_PER_RANK: '0'

NCCL_MNNVL_ENABLE: '1'
NCCL_CUMEM_ENABLE: '1'
SGLANG_MOONCAKE_CUSTOM_MEM_POOL: 'True'
MC_FORCE_MNNVL: '1'
SGLANG_DISAGGREGATION_BOOTSTRAP_TIMEOUT: '100000'
SGLANG_DISAGGREGATION_WAITING_TIMEOUT: '100000'
SGLANG_OPT_SWA_RELEASE_LEAF_LOCK_AFTER_WINDOW: '1'

decode_environment:
PYTHONUNBUFFERED: '1'
SGLANG_RADIX_DISABLE_REUSE: '1'
SGLANG_JIT_DEEPGEMM_FAST_WARMUP: '1'
SGLANG_DEFAULT_THINKING: '1'
SGLANG_DSV4_REASONING_EFFORT: max
SGLANG_OPT_SWA_SPLIT_LEAF_ON_INSERT: '1'
SGLANG_OPT_USE_JIT_NORM: '1'
SGLANG_OPT_USE_JIT_INDEXER_METADATA: '1'
SGLANG_OPT_USE_TOPK_V2: '1'

SGLANG_OPT_SWA_EVICT_DROP_PAGE_MARGIN: '1'
SGLANG_OPT_USE_FAST_MASK_EP: '1'
SGLANG_OPT_USE_DEEPGEMM_MEGA_MOE: '1'
SGLANG_OPT_FIX_HASH_MEGA_MOE: '1'
SGLANG_OPT_DEEPGEMM_MEGA_MOE_NUM_MAX_TOKENS_PER_RANK: '2048'
SGLANG_OPT_FIX_MEGA_MOE_MEMORY: '1'
SGLANG_OPT_FIX_NEXTN_MEGA_MOE: '1'
SGLANG_DEEPEP_NUM_MAX_DISPATCH_TOKENS_PER_RANK: '0'

NCCL_MNNVL_ENABLE: '1'
NCCL_CUMEM_ENABLE: '1'
SGLANG_MOONCAKE_CUSTOM_MEM_POOL: 'True'
MC_FORCE_MNNVL: '1'
SGLANG_DISAGGREGATION_BOOTSTRAP_TIMEOUT: '100000'
SGLANG_DISAGGREGATION_WAITING_TIMEOUT: '100000'
SGLANG_OPT_SWA_RELEASE_LEAF_LOCK_AFTER_WINDOW: '1'
SGLANG_OPT_USE_CUSTOM_ALL_REDUCE_V2: "0" # CAR_V2 is single-node only.
TORCH_DISTRIBUTED_DEFAULT_TIMEOUT: "1800"

sglang_config:
prefill:
served-model-name: deepseek-ai/DeepSeek-V4-Pro
model-path: "/model/"
trust-remote-code: true
tool-call-parser: deepseekv4

disaggregation-mode: prefill
disaggregation-transfer-backend: mooncake

tensor-parallel-size: 4
data-parallel-size: 4
expert-parallel-size: 4

enable-dp-attention: true
enable-dp-lm-head: true

moe-a2a-backend: deepep
deepep-config: '{"normal_dispatch":{"num_sms":96},"normal_combine":{"num_sms":96}}'

mem-fraction-static: 0.9
max-running-requests: 256
cuda-graph-max-bs: 256

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Dep8 prefill cap too low

Medium Severity

In disagg-1p1d-dep8-conc8192-mtp.yaml, prefill max-running-requests and cuda-graph-max-bs are set to 256 while the sibling disagg-1p1d-dep16-conc8192-mtp.yaml and disagg-2p1d-dep16-conc8192-mtp.yaml use 1024 for the same 1×TP4/EP4 prefill layout and the same benchmark concurrency of 8192. Prefill capacity should not shrink because decode TP differs, so this row likely bottlenecks prefill and skews high-concurrency results versus the other 8192 scenarios.

Fix in Cursor Fix in Web

Reviewed by Cursor Bugbot for commit e48f6b3. Configure here.

chunked-prefill-size: 32768
stream-interval: 60

decode:
served-model-name: deepseek-ai/DeepSeek-V4-Pro
model-path: "/model/"
trust-remote-code: true
tool-call-parser: deepseekv4

disaggregation-mode: decode
disaggregation-transfer-backend: mooncake

tensor-parallel-size: 8
data-parallel-size: 8
expert-parallel-size: 8

enable-dp-attention: true
enable-dp-lm-head: true

moe-a2a-backend: deepep
deepep-config: '{"normal_dispatch":{"num_sms":96},"normal_combine":{"num_sms":96}}'

speculative-algo: "EAGLE"
speculative-num-steps: 3
speculative-eagle-topk: 1
speculative-num-draft-tokens: 4

mem-fraction-static: 0.94
max-running-requests: 1536
Comment thread
cursor[bot] marked this conversation as resolved.
cuda-graph-max-bs: 256
swa-full-tokens-ratio: 0.15
context-length: 16384
stream-interval: 60

benchmark:
type: "sa-bench"
isl: 1024
osl: 1024
random_range_ratio: 0.8
concurrencies: "8192"
req_rate: "inf"
use_chat_template: true
custom_tokenizer: "sa_bench_tokenizers.sglang_deepseek_v4.SGLangDeepseekV4Tokenizer"
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