Data as of October 25, 2026 · How the score is built
Released Jul 16, 2026128K contextInclusionAI LLaDA2.2-flash model card
LLaDA2.2-flash
Decision readingLLaDA2.2-flash is tracked, but not publicly ranked yet. The profile exposes 8 sourced benchmark rows and leaves unsupported fields blank until a published record exists.
Released Jul 16, 2026 — see all recent releases
Decision snapshot
Each value carries a field reference instead of floating alone. Markers compare this model with the current ranked and priced catalog; they are not absolute quality thresholds.
Capability
Unranked
field median 50Not eligible for a public rank
Price
Self-hosted; infrastructure cost varies
input median $0.75No comparable first-party hosted token rate
Speed
Not measured
field median 96 tok/sTime to first token not measured
Context
128Ktokens
field median 256,000Maximum output length is tracked separately
Strongest published evidence
Published rows are visible, but no category has enough eligible evidence for a comparative rank.
Validate before choosing
8 published rows leave some tracked benchmark slots empty. No comparable first-party API token rate is published.
Source-linked · 8 displayable benchmark rows
Category score record
Scores and ranks appear only where published evidence can be displayed. The table keeps the score, weight, cohort, and evidence state together.
| Category | Score | Rank | Percentile | Weight | Benchmarks | Evidence |
|---|---|---|---|---|---|---|
| AgenticWeight 22%5 benchmarksVerified | Score pending | 5 benchmarks | Verified | |||
| CodingRank Not rankedWeight 20%3 benchmarksVerified | 20.0 | 3 benchmarks | Verified | |||
| ReasoningWeight 17%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| MultimodalWeight 12%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| KnowledgeWeight 12%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| MultilingualWeight 7%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| Inst. FollowingWeight 5%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| MathWeight 5%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured |
8 of 766 tracked benchmark slots have displayable evidence · bars run 0–100
Coverage detailsHow much of this is verified
Coverage is split by category so a strong number never hides a thin evidence base. Verified means the row is tied to a published source; provisional rows remain visible but separate.
- Agentic5/5 verified
- Coding3/3 verified
- ReasoningNot measured
- MultimodalNot measured
- KnowledgeNot measured
- MultilingualNot measured
- Inst. FollowingNot measured
- MathNot measured
Benchmark ledger
Coding opens by default. The marker compares each value with the best source-verified result in the catalog; provisional leaders do not set the reference. Expand the remaining categories for every published row.
Coding3 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| SWE-bench Pro | Score30.1% | Versus best verified row Best verified: Claude Opus 5.5 · 89.9% | Gap59.8 behind | WeightDisplay only | Provider exact |
| SWE Multilingual | Score25% | Versus best verified row Best verified: Claude Opus 5.5 · 93.9% | Gap68.9 behind | WeightDisplay only | Provider exact |
| SWE-bench VerifiedSoftware Engineering Benchmark Verified | Score49.3% | Versus best verified row Best verified: Claude Opus 5 · 96% | Gap46.7 behind | WeightDisplay only | Provider exact |
Agentic5 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| MCP Atlas | Score46.2% | Versus best verified row Best verified: Muse Spark Open · 89.2% | Gap43 behind | WeightDisplay only | Provider exact |
| BFCL v4Berkeley Function Calling Leaderboard v4 | Score60.8% | Versus best verified row Best verified: BTL-3 · 88.5% | Gap27.7 behind | WeightDisplay only | Provider exact |
| τ²-bench resultsτ²-Bench Tool-Agent-User Evaluation | Score80.3% | Versus best verified row Best verified: GPT-5.4 · 98.9% | Gap18.6 behind | WeightDisplay only | Provider exact |
| Claw-Eval | Score64.2% | Versus best verified row Best verified: Ornith-1.5-397B · 81.4% | Gap17.2 behind | WeightDisplay only | Provider exact |
| PinchBench | Score81.7% | Versus best verified row Best verified: Pokee-Isaac 28B · 95.7% | Gap14 behind | WeightDisplay only | Provider exact |
Bars run 0–100; the dark tick marks the best source-verified value
All 8 rowsLineage
The sequence follows explicit supersedes links. Each score is estimated for that model; a relative can inform a sparse estimate but never sets a floor, so a newer release can score below an earlier one. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.
Flash
LLaDA2.2-miniSpec sheet
Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.
- API model ID
- inclusionAI/LLaDA2.2-flashInclusionAI LLaDA2.2-flash model card
- Context window
- 128KInclusionAI LLaDA2.2-flash model card
- Maximum output
- Not sourced yet
- Knowledge cutoff
- Not sourced yet
- Input modalities
- Not sourced yet
- Output modalities
- Not sourced yet
- Parameters
- Not sourced yet
- Availability
- InclusionAI publishes the 100B-class agent-oriented MoE diffusion language model under Apache 2.0 on Hugging Face with a 128K context, Levenshtein-editing DELETE and INSERT tokens, block routing, and SGLang serving.
- Cloud regions
- Not tracked yet
- Lifecycle
- Current
- API capabilities
- Tool calling, structured outputs, and batch support are not tracked yet
- Prompt caching
- Not documented in the pricing recordInclusionAI LLaDA2.2-flash model card
- Self-host
- Open weights available; hardware estimate not sourced
- Rate limits
- Not tracked yet
How to read this profile
The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.
We track LLaDA2.2-flash, but the public leaderboard excludes this profile until enough non-generated benchmark coverage is available. Only published rows appear above.
LLaDA2.2-flash is a open weight model with a 128K context window. It uses an explicit reasoning mode, which can improve complex problem solving while adding latency and token use.
InclusionAI publishes the 100B-class agent-oriented MoE diffusion language model under Apache 2.0 on Hugging Face with a 128K context, Levenshtein-editing DELETE and INSERT tokens, block routing, and SGLang serving.
Official exact-value snapshot from the LLaDA2.2-flash Hugging Face model card (July 16, 2026), evaluated at a 128K context. BenchLM maps SWE-bench Verified, SWE-bench Pro, SWE-bench Multilingual, τ²-Bench, Claw-Eval, PinchBench, MCP-Atlas, and BFCL-V4 onto existing lanes and keeps the throughput (TPS) table descriptive. Provider-run rows keep the diffusion model unranked.
LLaDA2.2-flash sits in the LLaDA2.2 family with LLaDA2.2-mini. 8 of 766 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.
Last updated October 25, 2026. Runtime fields remain blank until a sourced snapshot exists.
Deployment options
Self-host and provider-specific paths stay separate from benchmark evidence so operating constraints are visible before a score becomes the whole decision.
Published weights are available, but BenchLM does not yet have a sourced parameter and VRAM profile for this exact model. Hardware cost estimates stay unavailable until that sizing record is complete.
Estimate VRAM from known parametersQuestions
How does LLaDA2.2-flash perform overall in AI benchmarks?
LLaDA2.2-flash has 8 source-displayable benchmark rows, but it does not qualify for a public overall rank. The available rows remain visible by category without being converted into a site-wide score. Missing evidence stays blank instead of being estimated from an earlier model.
Is LLaDA2.2-flash good for coding and programming?
LLaDA2.2-flash has source-displayable benchmark coverage for coding and programming, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
Is LLaDA2.2-flash good for agentic tool use and computer tasks?
LLaDA2.2-flash has source-displayable benchmark coverage for agentic tool use and computer tasks, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
Is LLaDA2.2-flash open source?
LLaDA2.2-flash is an open-weight model from InclusionAI. Its weights can be downloaded for local or hosted deployment, subject to the published license. Open weight does not automatically mean open source: training data and training code may remain private, and commercial restrictions can still apply.
Which sibling models are related to LLaDA2.2-flash?
LLaDA2.2-flash belongs to the LLaDA2.2 family. Related tracked variants include LLaDA2.2-mini. A sibling link indicates shared lineage or a documented configuration relationship; it does not mean the variants have identical pricing, context limits, benchmark evidence, or deployment behavior. Compare before switching.
Does LLaDA2.2-flash have full benchmark coverage on BenchLM?
No. LLaDA2.2-flash currently has 8 source-displayable rows. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.
What is the context window size of LLaDA2.2-flash?
LLaDA2.2-flash has a documented context window of 128K. That figure is the maximum combined prompt and retained-conversation space reported for this exact model; it is not the maximum output length. The profile keeps output limits separate because providers often publish those limits independently.