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Model profile · InclusionAI

Ling 3.0 Flash FP8

Released Aug 4, 2026 see all recent releases

Ling 3.0 Flash FP8 is tracked, but not publicly ranked yet. The profile exposes 4 sourced benchmark rows and leaves unsupported fields blank until a published record exists.

Data as of August 4, 2026 · How the score is built

Strongest published evidence

Instruction Following ranks #22. A well-rounded choice across a range of tasks.

Validate before choosing

4 published rows leave some tracked benchmark slots empty. No comparable first-party API token rate is published.

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 57.3

Not eligible for a public rank

Price

API rate not published

input median $1

No comparable first-party hosted token rate

Speed

Not measured

field median 92 tok/s

Time to first token not measured

Context

262Ktokens

field median 200,000

Maximum output length is tracked separately

How 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.

  1. AgenticNot measured
  2. Coding1/1 verified
  3. ReasoningNot measured
  4. Knowledge2/2 verified
  5. MathNot measured
  6. MultilingualNot measured
  7. MultimodalNot measured
  8. Inst. Following1/1 verified
Verified sourceProvisionalNot measured

Spec sheet

Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.

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 blockwise FP8 checkpoint under the MIT License on Hugging Face. The repository documents two-GPU SGLang serving and the same 262,144-token context as the BF16 checkpoint.
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 Ling 3.0 Flash FP8 model card
Self-host
Open weights available; hardware estimate not sourced
Rate limits
Not tracked yet

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 parameters

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 scores, ranks, weighting, benchmark coverage, and evidence status
CategoryScore
AgenticWeight 22%0 benchmarksNot measuredNot measured
CodingRank #59 of 131Percentile 55thWeight 20%1 benchmarkVerified50.5
ReasoningWeight 17%0 benchmarksNot measuredNot measured
KnowledgeRank Not rankedWeight 12%2 benchmarksVerified72.5
MathWeight 5%0 benchmarksNot measuredNot measured
MultilingualWeight 7%0 benchmarksNot measuredNot measured
MultimodalWeight 12%0 benchmarksNot measuredNot measured
Inst. FollowingRank #22 of 36Percentile 40thWeight 5%1 benchmarkVerified76.3

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.

Coding1 row
Coding benchmark values, best verified comparison, weight, and source status
SciCodeScientific Code BenchmarkScore40.4%Versus best verified row

Best verified: Sakana Fugu · 60.1%

Gap19.7 behindWeightWeighted 16%
Knowledge2 rows
Knowledge benchmark values, best verified comparison, weight, and source status
GPQAGraduate-Level Google-Proof Q&AScore84%Versus best verified row

Best verified: Sakana Fugu-Ultra · 95.5%

Gap11.5 behindWeightWeighted 7%
GPQA-DGPQA DiamondScore84.0%Versus best verified row

Best verified: Sakana Fugu-Ultra · 95.5%

Gap11.5 behindWeightDisplay only
Inst. Following1 row
Inst. Following benchmark values, best verified comparison, weight, and source status
IFBenchInstruction Following BenchmarkScore73.4%Versus best verified row

Best verified: MAI-Thinking-1 · 85%

Gap11.6 behindWeightWeighted 65%

Lineage

The sequence follows explicit supersedes links. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.

flash-fp8 · FP8

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 Ling 3.0 Flash FP8, but the public leaderboard excludes this profile until enough non-generated benchmark coverage is available. Only published rows appear above.

Ling 3.0 Flash FP8 is a open weight model with a 262K context window. It uses an explicit reasoning mode, which can improve complex problem solving while adding latency and token use.

InclusionAI publishes the blockwise FP8 checkpoint under the MIT License on Hugging Face. The repository documents two-GPU SGLang serving and the same 262,144-token context as the BF16 checkpoint.

Official exact-value quantization snapshot from InclusionAI's Ling-3.0-flash-fp8 Hugging Face model card. The card independently evaluates the blockwise FP8 checkpoint on GPQA-Diamond, IFBench, SciCode, and ArcPrize. BenchLM maps the first three to exact existing keys and leaves ArcPrize outside the schema. The row remains non-ranking because the FP8-specific evidence covers only three supported benchmark families; no BF16 launch-table scores are copied onto the quantized variant.

Ling 3.0 Flash FP8 sits in the Ling 3.0 family with Ling 3.0 Flash. 4 of 381 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.

Its strongest eligible category is Instruction Following at #22, while its lowest eligible position is Coding at #59. a well-rounded choice across a range of tasks.

Radar

Ling 3.0 Flash FP8 release history

Full release history

Frequently asked questions

How does Ling 3.0 Flash FP8 perform overall in AI benchmarks?

Ling 3.0 Flash FP8 has 4 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 Ling 3.0 Flash FP8 good for knowledge and understanding?

Ling 3.0 Flash FP8 has source-displayable benchmark coverage for knowledge and understanding, 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 Ling 3.0 Flash FP8 good for coding and programming?

Ling 3.0 Flash FP8 ranks #59 out of 131 eligible models for coding and programming, with a public category score of 50.5/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.

Is Ling 3.0 Flash FP8 good for instruction following?

Ling 3.0 Flash FP8 ranks #22 out of 36 eligible models for instruction following, with a public category score of 76.3/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.

Is Ling 3.0 Flash FP8 open source?

Ling 3.0 Flash FP8 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 Ling 3.0 Flash FP8?

Ling 3.0 Flash FP8 belongs to the Ling 3.0 family. Related tracked variants include Ling 3.0 Flash. 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 Ling 3.0 Flash FP8 have full benchmark coverage on BenchLM?

No. Ling 3.0 Flash FP8 currently has 4 source-displayable rows across 381 tracked benchmark slots. 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 Ling 3.0 Flash FP8?

Ling 3.0 Flash FP8 has a documented context window of 262K. 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.

Last updated August 4, 2026. Runtime fields remain blank until a sourced snapshot exists.

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