IndexShare
IndexShare is a sparse-attention optimization that reuses one token-selection indexer across a group of transformer layers instead of recomputing it at every layer, cutting the redundant compute that dominates cost once context stretches past hundreds of thousands of tokens.
Zhipu AI's Z.ai introduced the technique in the GLM-5.2 technical writeup on June 17, 2026, four days after the 753-billion-parameter model shipped: one indexer now serves every four sparse-attention layers, cutting per-token FLOPs 2.9x at 1M-token context, and the same sharing trick lifts MTP speculative-decoding acceptance length up to 20%.
GLM-5.2 groups every four sparse-attention layers under one shared indexer instead of recomputing the top-k selection at each layer — cutting the indexer's dot-product-and-top-k step to one call per group of four, which Zhipu AI credits for making 1M-token inference affordable enough to ship as the model's default context window.
Like a delivery driver who scouts the route once, then reuses it for the next four stops instead of re-checking the map every time.
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Why is it emerging now?
Z.ai's open-weight GLM-5.2, shipped June 13, 2026, turned IndexShare into 2026's most-discussed attention-efficiency trick: one sparse-attention indexer shared across four layers cuts per-token FLOPs 2.9x at 1M-token context. The technique underpins claims that GLM-5.2 matches Claude Opus 4.8 and beats GPT-5.5 on coding benchmarks at a fraction of the API cost.
Search Interest
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Nascent0–7 days
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Emergent8–30 days
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Validating ← now31–90 days
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Rising91–180 days
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Established180 days +
Outlook
6-month signal projection and commercial timeline.
Zhipu's indexer-sharing trick landed as DeepSeek Sparse Attention went industry-wide; expect a rival lab to ship a named equivalent within two quarters.
Risk · If DSA loses out to a different sparse-attention design, IndexShare stays a GLM-only footnote rather than industry vocabulary.
Analogs · MTP (multi-token prediction) · Grouped-Query Attention (GQA) · Mixture-of-Experts (MoE)
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nowExplainer SERP wide open
Only ML blogs cover it; no dedicated comparison or tool content yet.
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3-6moRival labs test the trick
DeepSeek, Kimi, MiniMax likely test indexer-sharing in next releases.
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6-12moStandard architecture vocabulary
If adopted broadly, cited alongside MoE and GQA in model comparisons.
Competition & Opportunity for term “IndexShare”
Signals derived from the tracked queries, the term's monetization cards, and its cluster neighbors. Heuristic except where marked measured (Google KD).
Ideas for term “IndexShare”
Buildable pitches — turn this term into an article, site, product, post, newsletter, video, or course. Steal any card and run with it.
No deep, non-ML-blog explainer ranks yet for the plain-English 'what is IndexShare' query — wide-open SEO window while the term is still confined to Raschka-style technical posts.
A comparison piece slotting IndexShare next to Multi-Token Prediction and Grouped-Query Attention serves the exact 'X vs Y' query pattern long-context engineers search when picking a serving stack.
Self-hosters hitting the mlx-lm 'missing per-layer indexer params' load error need a plain guide to IndexShare's per-layer weight requirements before serving GLM-5.2 on consumer GPUs.
vLLM/SGLang/mlx-lm users keep hitting silent load failures from missing per-layer indexer params — a pre-flight checker for indie infra engineers running open-weight models.
Three labs are already forking Zhipu's four-layer indexer trick before GLM-5.3 even ships.
While frontier labs sell '1M context' as a spec-sheet number, GLM-5.2 shipped the one architecture change that actually makes it affordable.
I fed it an 800K-token codebase and timed every response against Claude Opus 4.8 — the compute savings showed up exactly where the docs said, and nowhere else.
What People Search
Long-tail queries from Google Suggest + Trends. Volume and competition are heuristics — directional, not audited. Content Type comes from query shape.
SERP of term “IndexShare”
What searchers see today — organic results on top, paid ads if anyone's bidding. Ad density is a real-time commercial signal.
FAQ
What is IndexShare?
IndexShare is a sparse-attention optimization that reuses one token-selection indexer across a group of transformer layers instead of recomputing it at every layer, cutting the redundant compute that dominates cost once context stretches….
Why is IndexShare emerging now?
Z.ai's open-weight GLM-5.2, shipped June 13, 2026, turned IndexShare into 2026's most-discussed attention-efficiency trick: one sparse-attention indexer shared across four layers cuts per-token FLOPs 2.9x at 1M-token context. The technique underpins claims that GLM-5.2 matches Claude Opus 4.8 and beats GPT-5.5 on coding benchmarks at a fraction of the API cost.
When did IndexShare emerge?
Publicly emerged around 2026-06-17 (about 55 days ago as of 2026-08-11). EarlyTerms first recorded a pipeline signal on 2026-06-18.
Related Terms
Other terms in the same space — aliases, subtypes, competitors, and neighbors to explore next.
- Part of GLM-5.2 GLM-5.2 is Z.ai's (Zhipu AI) 744-billion-parameter open-weight Mixture-of-Experts model engineered for long-horizon coding and… →
- Competitor Claude Opus 4.8 Claude Opus 4.8 is Anthropic's latest flagship LLM, released May 28, 2026 at unchanged pricing ($5/$25 per million tokens). →
- Competitor GPT-5.5 GPT-5.5 is OpenAI's frontier language model released on April 23, 2026 — the first fully retrained base model since GPT-4.5, with every… →
- Competitor Kimi K2.6 Kimi K2.6 is Moonshot AI's April 20, 2026 open-weight flagship — a 1T-parameter Mixture-of-Experts model (32B active, 384 experts, 256K… →
- Competitor MiniMax-M3 MiniMax M3 is a 428B-parameter Mixture-of-Experts large language model from Shanghai-based MiniMax (稀宇科技), activating 22B parameters per… →
- Related MTP MTP (Multi-Token Prediction) is an inference acceleration technique that lets a lightweight drafter model predict several future tokens… →
- Related DeepSeek V4 Pro DeepSeek V4 Pro is the premium tier of DeepSeek's V4 series: a 1.6-trillion-parameter, 49-billion-active Mixture-of-Experts model with a… →
- Related Context Window A context window is the span of tokens an LLM reads and reasons over in a single forward pass. →
- Related Context Rot Context rot is the measurable degradation in large-language-model output quality as input length grows, even when the prompt stays well… →
- Related Agentic Coding Agentic coding is the software-development pattern where an autonomous AI agent plans, writes, tests, and iterates on code against a… →
- Related Coding Agents Coding Agents is the category name for AI developer tools that act on code autonomously — reading a repo, planning a change, editing… →
- Related GLM-5.1 GLM-5.1 is Z.ai's 754-billion-parameter open-weight large language model, purpose-built for agentic engineering and long-horizon coding… →
Sources
Primary URLs this report cites — open any to verify the claim yourself.
- 01 Z.ai — GLM-5.2: Built for Long-Horizon Tasks (official blog) z.ai ↗
- 02 Sebastian Raschka — GLM-5.2 IndexShare Architecture Note sebastianraschka.com ↗
- 03 MindStudio — What Is Index Share? mindstudio.ai ↗
- 04 VentureBeat — Z.ai's open-weights GLM-5.2 beats GPT-5.5 for 1/6th the cost venturebeat.com ↗
- 05 Hacker News — GLM 5.2 beats Claude in our benchmarks news.ycombinator.com ↗
- 06 GitHub zai-org/GLM-5 Issue #94 — IndexShare stress-testing proposal github.com ↗
- 07 PhantomByte — The 1M Context Mirage: What IndexShare Actually Delivers articles.phantom-byte.com ↗