docs: sync LMSYS SGLang blog cards (#27322)

Co-authored-by: sglang-bot <sglang-bot@users.noreply.github.com>
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sglang-bot
2026-06-04 17:42:09 -07:00
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co-authored by sglang-bot
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@@ -82,6 +82,226 @@ It is designed to deliver low-latency and high-throughput inference across a wid
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>
<a
href="https://lmsys.org/blog/2026-06-04-nvidia-run-nemotron-3-ultra/"
target="_blank"
rel="noopener noreferrer"
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>
<div
style={{
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>
<img
src="https://lmsys.org/images/blog/nemotron-3-ultra/image1.png"
alt="SGLang and Miles Add Day-0 Support for NVIDIA Nemotron 3 Ultra for Long-Running Autonomous Agents"
style={{
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</div>
<div style={{ padding: "0.9rem 1rem 1rem" }}>
<p
style={{
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>
{"SGLang and Miles Add Day-0 Support for NVIDIA Nemotron 3 Ultra for Long-Running Autonomous Agents"}
</p>
<p
style={{
margin: "0.55rem 0 0",
fontSize: "0.85rem",
opacity: 0.75,
}}
>
{"June 4, 2026"}
</p>
</div>
</a>
<a
href="https://lmsys.org/blog/2026-06-04-higgs-audio-v3-tts/"
target="_blank"
rel="noopener noreferrer"
style={{
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>
<div
style={{
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>
<img
src="https://sgl-project.github.io/sglang-omni/_images/higgs-architecture.png"
alt="Higgs Audio v3 TTS on SGLang-Omni: Real-Time, Controllable Speech for Voice Agents"
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</div>
<div style={{ padding: "0.9rem 1rem 1rem" }}>
<p
style={{
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lineHeight: 1.35,
fontSize: "0.98rem",
}}
>
{"Higgs Audio v3 TTS on SGLang-Omni: Real-Time, Controllable Speech for Voice Agents"}
</p>
<p
style={{
margin: "0.55rem 0 0",
fontSize: "0.85rem",
opacity: 0.75,
}}
>
{"June 4, 2026"}
</p>
</div>
</a>
<a
href="https://lmsys.org/blog/2026-06-01-hetero-epd/"
target="_blank"
rel="noopener noreferrer"
style={{
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height: "100%",
}}
>
<div
style={{
aspectRatio: "16 / 9",
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background: "rgba(128, 128, 128, 0.15)",
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>
<img
src="https://lmsys.org/images/blog/hetero-epd/1.png"
alt="Heterogeneous CPU + GPU EPD Disaggregation to Boost VLM Serving"
style={{
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</div>
<div style={{ padding: "0.9rem 1rem 1rem" }}>
<p
style={{
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lineHeight: 1.35,
fontSize: "0.98rem",
}}
>
{"Heterogeneous CPU + GPU EPD Disaggregation to Boost VLM Serving"}
</p>
<p
style={{
margin: "0.55rem 0 0",
fontSize: "0.85rem",
opacity: 0.75,
}}
>
{"May 29, 2026"}
</p>
</div>
</a>
<a
href="https://lmsys.org/blog/2026-05-28-mori/"
target="_blank"
rel="noopener noreferrer"
style={{
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}}
>
<div
style={{
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background: "rgba(128, 128, 128, 0.15)",
}}
>
<img
src="https://lmsys.org/images/blog/mori/tco1-new.png"
alt="Win on TCO: How AMD Instinct\u2122 MI355X Achieves Cost-Competitive Distributed Inference Through SGLang with MoRI"
style={{
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</div>
<div style={{ padding: "0.9rem 1rem 1rem" }}>
<p
style={{
margin: 0,
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lineHeight: 1.35,
fontSize: "0.98rem",
}}
>
{"Win on TCO: How AMD Instinct\u2122 MI355X Achieves Cost-Competitive Distributed Inference Through SGLang with MoRI"}
</p>
<p
style={{
margin: "0.55rem 0 0",
fontSize: "0.85rem",
opacity: 0.75,
}}
>
{"May 28, 2026"}
</p>
</div>
</a>
<a
href="https://lmsys.org/blog/2026-04-29-p2p-update/"
target="_blank"
@@ -192,226 +412,6 @@ It is designed to deliver low-latency and high-throughput inference across a wid
</p>
</div>
</a>
<a
href="https://lmsys.org/blog/2026-04-10-sglang-hisparse/"
target="_blank"
rel="noopener noreferrer"
style={{
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>
<div
style={{
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background: "rgba(128, 128, 128, 0.15)",
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>
<img
src="https://lmsys.org/images/blog/hisparse/hisparse_overview.png"
alt="HiSparse: Turbocharging Sparse Attention with Hierarchical Memory"
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</div>
<div style={{ padding: "0.9rem 1rem 1rem" }}>
<p
style={{
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lineHeight: 1.35,
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>
{"HiSparse: Turbocharging Sparse Attention with Hierarchical Memory"}
</p>
<p
style={{
margin: "0.55rem 0 0",
fontSize: "0.85rem",
opacity: 0.75,
}}
>
{"April 10, 2026"}
</p>
</div>
</a>
<a
href="https://lmsys.org/blog/2026-03-25-gtc2026/"
target="_blank"
rel="noopener noreferrer"
style={{
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>
<div
style={{
aspectRatio: "16 / 9",
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background: "rgba(128, 128, 128, 0.15)",
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>
<img
src="https://lmsys.org/images/blog/gtc2026/happyhour-crowd.jpg"
alt="Highlights of SGLang at NVIDIA GTC 2026"
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</div>
<div style={{ padding: "0.9rem 1rem 1rem" }}>
<p
style={{
margin: 0,
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lineHeight: 1.35,
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>
{"Highlights of SGLang at NVIDIA GTC 2026"}
</p>
<p
style={{
margin: "0.55rem 0 0",
fontSize: "0.85rem",
opacity: 0.75,
}}
>
{"March 31, 2026"}
</p>
</div>
</a>
<a
href="https://lmsys.org/blog/2026-03-25-eep-partial-failure-tolerance/"
target="_blank"
rel="noopener noreferrer"
style={{
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}}
>
<div
style={{
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>
<img
src="https://lmsys.org/images/blog/eep-partial-failure-tolerance/figure.png"
alt="Elastic EP in SGLang: Achieving Partial Failure Tolerance for DeepSeek MoE Deployments"
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</div>
<div style={{ padding: "0.9rem 1rem 1rem" }}>
<p
style={{
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>
{"Elastic EP in SGLang: Achieving Partial Failure Tolerance for DeepSeek MoE Deployments"}
</p>
<p
style={{
margin: "0.55rem 0 0",
fontSize: "0.85rem",
opacity: 0.75,
}}
>
{"March 25, 2026"}
</p>
</div>
</a>
<a
href="https://lmsys.org/blog/2026-03-17-rocm-miles-rl-amd/"
target="_blank"
rel="noopener noreferrer"
style={{
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}}
>
<div
style={{
aspectRatio: "16 / 9",
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background: "rgba(128, 128, 128, 0.15)",
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>
<img
src="https://lmsys.org/images/blog/rocm_miles_rl/fig_1.png"
alt="ROCm Support for Miles: Large-Scale RL Post-Training on AMD Instinct\u2122 GPUs"
style={{
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</div>
<div style={{ padding: "0.9rem 1rem 1rem" }}>
<p
style={{
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lineHeight: 1.35,
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>
{"ROCm Support for Miles: Large-Scale RL Post-Training on AMD Instinct\u2122 GPUs"}
</p>
<p
style={{
margin: "0.55rem 0 0",
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opacity: 0.75,
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>
{"March 17, 2026"}
</p>
</div>
</a>
</div>
</div>
{/* END_LMSYS_SGLANG_BLOG_CARDS */}