Ling 3.0 Flash FP8 vs Qwen3.6-35B-A3B

Decision reading

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.

1 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A

Ling 3.0 Flash FP8

InclusionAI

—

Evidence status unavailable

90% interval unavailable

Model B

Qwen3.6-35B-A3B

Alibaba

43.85/100

Estimated · Public rank #162

90% interval 37.4–50.3

Updated September 18, 2026. We do not rank this pair: at least one has no public score. Public scores include evidence status and uncertainty.

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Which one for your work

Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.

No workload recommendation clears the current evidence threshold.

Use the matched evidence, workload costs, and sourced specifications below instead of treating a point score as a universal answer.

Show secondary and unsupported calls

Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Ling 3.0 Flash FP8 is not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Ling 3.0 Flash FP8 is not ranked on the public lane for agentic, so no winner is named for agentic.
Confidence: limited
Long documents
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
Confidence: documented
Chat turn cost
1K fresh input + 500 output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
Repository review cost
50K fresh input + 3K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates

Which one for a specific job

Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.

Pick the job you would use them for

The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.

—Ling 3.0 Flash FP845.0Qwen3.6-35B-A3B

Not comparable · BenchAlign

The coding row is not comparable on the public lane: at least one model is not measured or not ranked there.

Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.

Open the coding leaderboard Shortlist models for this job

What is actually comparable

Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.

3 Ling 3.0 Flash FP8 only

1 Shared

40 Qwen3.6-35B-A3B only

Shared results: 1
Ling 3.0 Flash FP8 only: 3
Qwen3.6-35B-A3B only: 40
Like-for-like categories: 0 / 8

1 category rests on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.

Instruction following

Directional only

Ling 3.0 Flash FP8: 69.7; #65/124
Qwen3.6-35B-A3B: 76.8; #58/124
Basis: Provisional lane · 1 vs 0 weighted rows
Reading: Directional only

Agentic

Not comparable

Ling 3.0 Flash FP8: Not ranked
Qwen3.6-35B-A3B: 40.2; Estimated · #119/154
Basis: BenchAlign lane · 0 vs 11 public rows
Reading: Not comparable

Coding

Not comparable

Ling 3.0 Flash FP8: Not ranked
Qwen3.6-35B-A3B: 45.0; Estimated · #93/154
Basis: BenchAlign lane · 1 vs 6 public rows
Reading: Not comparable

Reasoning

Not comparable

Ling 3.0 Flash FP8: Not ranked
Qwen3.6-35B-A3B: 70.3; Unranked · 2 rankable rows
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Knowledge

Not comparable

Ling 3.0 Flash FP8: Not ranked
Qwen3.6-35B-A3B: 44.3; Estimated · #118/184
Basis: BenchAlign lane · 2 vs 5 public rows
Reading: Not comparable

Math

Not comparable

Ling 3.0 Flash FP8: Not ranked
Qwen3.6-35B-A3B: 70.7; Unranked · 5 rankable rows
Basis: Provisional lane · 0 vs 2 weighted rows
Reading: Not comparable

Multilingual

Not comparable

Ling 3.0 Flash FP8: Not ranked
Qwen3.6-35B-A3B: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Multimodal

Not comparable

Ling 3.0 Flash FP8: Not ranked
Qwen3.6-35B-A3B: 50.0; #37/48
Basis: Provisional lane · 0 vs 2 weighted rows
Reading: Not comparable

Category scores with the server-provided evidence basis for Ling 3.0 Flash FP8 and Qwen3.6-35B-A3B
Category	Ling 3.0 Flash FP8	Qwen3.6-35B-A3B	Basis	Reading
Instruction following	69.7#65/124	76.8#58/124	Directional onlyProvisional lane · 1 vs 0 weighted rows	Directional only
Agentic	Not ranked	40.2Estimated · #119/154	Not comparableBenchAlign lane · 0 vs 11 public rows	Not comparable
Coding	Not ranked	45.0Estimated · #93/154	Not comparableBenchAlign lane · 1 vs 6 public rows	Not comparable
Reasoning	Not ranked	70.3Unranked · 2 rankable rows	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable
Knowledge	Not ranked	44.3Estimated · #118/184	Not comparableBenchAlign lane · 2 vs 5 public rows	Not comparable
Math	Not ranked	70.7Unranked · 5 rankable rows	Not comparableProvisional lane · 0 vs 2 weighted rows	Not comparable
Multilingual	Not ranked	Not ranked	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable
Multimodal	Not ranked	50.0#37/48	Not comparableProvisional lane · 0 vs 2 weighted rows	Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

Shape of the matched evidence

Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.

Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.

GPQA
Knowledge
Ling 3.0 Flash FP8: 84%Qwen3.6-35B-A3B: 86%Normalized gap 2.0Ling 3.0 Flash FP8 source Qwen3.6-35B-A3B source

What each workload costs

Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.

Chat turn

1K fresh input + 500 output tokens

Ling 3.0 Flash FP8: API rate not published; Fits in one request
Qwen3.6-35B-A3B: API rate not published; Fits in one request

Ling 3.0 Flash FP8 has no comparable published API token rate. Qwen3.6-35B-A3B has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Ling 3.0 Flash FP8: API rate not published; Fits in one request
Qwen3.6-35B-A3B: API rate not published; Fits in one request

Ling 3.0 Flash FP8 has no comparable published API token rate. Qwen3.6-35B-A3B has no comparable published API token rate.

Cache-heavy agent loop

200K cached + 20K fresh input + 10K output tokens

Ling 3.0 Flash FP8: API rate not published; Fits in one request; Cached-input rate unavailable
Qwen3.6-35B-A3B: API rate not published; Fits in one request; Cached-input rate unavailable

Ling 3.0 Flash FP8 has no comparable published API token rate. Qwen3.6-35B-A3B has no comparable published API token rate.

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

SpecificationLing 3.0 Flash FP8Qwen3.6-35B-A3B

Context window

Maximum documented context; output-token limits may be lower.

Ling 3.0 Flash FP8

262K

InclusionAI Ling 3.0 Flash FP8 model card

Qwen3.6-35B-A3B

262K

API model ID

Ling 3.0 Flash FP8

Not sourced

Qwen3.6-35B-A3B

Not sourced

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

Ling 3.0 Flash FP8

No comparable hosted API rate

InclusionAI Ling 3.0 Flash FP8 model card

Qwen3.6-35B-A3B

No comparable hosted API rate

Documented inputs

Ling 3.0 Flash FP8

Not sourced

Qwen3.6-35B-A3B

Not sourced

Documented outputs

Ling 3.0 Flash FP8

Not sourced

Qwen3.6-35B-A3B

Not sourced

Provider availability

Ling 3.0 Flash FP8

Not sourced

Qwen3.6-35B-A3B

Not sourced

Reasoning profile

Ling 3.0 Flash FP8

Reasoning

Qwen3.6-35B-A3B

Reasoning

Weight access

Ling 3.0 Flash FP8

Open Weight

Qwen3.6-35B-A3B

Open Weight

License

Ling 3.0 Flash FP8

Open Weight

Qwen3.6-35B-A3B

Open Weight

Release date

Ling 3.0 Flash FP8

2026-08-04

Qwen3.6-35B-A3B

2026-04-15

If you already use one of these models

Deployment change: The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
Quality signal: At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
Workload cost: A complete comparable API-rate estimate is not available for both models.
Context tradeoff: Both models list 262K.

Run the same representative tasks against both endpoints before changing production traffic.

Benchmark evidence

The full public result ledger is available for audit without forcing a wide desktop table onto a phone.

Browse raw public benchmark evidence44 rows

Agentic

Terminal-Bench 2.0
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B51.5%
Source
Not directly comparable
Claw-Eval
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B68.7%
Source
Not directly comparable
QwenClawBench
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B52.6%
Source
Not directly comparable
QwenWebBench
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B1397
Source
Not directly comparable
τ³-bench results
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B67.2%
Source
Not directly comparable
VITA-Bench
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B35.6%
Source
Not directly comparable
DeepPlanning
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B25.9%
Source
Not directly comparable
Toolathlon
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B26.9%
Source
Not directly comparable
MCP Atlas
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B62.8%
Source
Not directly comparable
WideResearch
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B60.1%
Source
Not directly comparable
Gert Labs
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B42.65%
Source
Not directly comparable

Coding

SciCode
Ling 3.0 Flash FP840.4%
Source
Qwen3.6-35B-A3B—
Not directly comparable
SWE-bench Verified
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B73.4%
Source
Not directly comparable
SWE Multilingual
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B67.2%
Source
Not directly comparable
SWE-bench Pro
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B49.5%
Source
Not directly comparable
Terminal-Bench 2.0
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B51.5%
Source
Not directly comparable
LiveCodeBench
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B80.4%
Source
Not directly comparable
NL2Repo
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B29.4%
Source
Not directly comparable

Knowledge

GPQA
Ling 3.0 Flash FP884%
Source
Qwen3.6-35B-A3B86%
Source
Qwen3.6-35B-A3B leads this result
GPQA-D
Ling 3.0 Flash FP884.0%
Source
Qwen3.6-35B-A3B—
Not directly comparable
MMLU-Pro
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B85.2%
Source
Not directly comparable
SuperGPQA
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B64.7%
Source
Not directly comparable
C-Eval
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B90%
Source
Not directly comparable
HLE
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B21.4%
Source
Not directly comparable

Math

HMMT Feb 2025
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B90.7%
Source
Not directly comparable
HMMT Nov 2025
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B89.1%
Source
Not directly comparable
HMMT Feb 2026
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B83.6%
Source
Not directly comparable
MMAnswerBench
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B78.9%
Source
Not directly comparable
AIME26
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B92.7%
Source
Not directly comparable

Multimodal

MMMU
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B81.7%
Source
Not directly comparable
MMMU-Pro
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B75.3%
Source
Not directly comparable
RealWorldQA
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B85.3%
Source
Not directly comparable
OmniDocBench 1.5
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B89.9%
Source
Not directly comparable
CharXiv
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B78%
Source
Not directly comparable
SimpleVQA
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B58.9%
Source
Not directly comparable
CC-OCR
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B81.9%
Source
Not directly comparable
AI2D_TEST
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B92.7%
Source
Not directly comparable
RefCOCO (avg)
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B92.0%
Source
Not directly comparable
ODINW13
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B50.8%
Source
Not directly comparable
Video-MME (with subtitle)
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B86.6%
Source
Not directly comparable
Video-MME (w/o subtitle)
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B82.5%
Source
Not directly comparable
VideoMMMU
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B83.7%
Source
Not directly comparable
MLVU (M-Avg)
Ling 3.0 Flash FP8—
Qwen3.6-35B-A3B86.2%
Source
Not directly comparable

Instruction following

IFBench
Ling 3.0 Flash FP873.4%
Source
Qwen3.6-35B-A3B—
Not directly comparable

Questions

Which is better, Ling 3.0 Flash FP8 or Qwen3.6-35B-A3B?

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Ling 3.0 Flash FP8 or Qwen3.6-35B-A3B?

Ling 3.0 Flash FP8 is not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, Ling 3.0 Flash FP8 or Qwen3.6-35B-A3B?

Ling 3.0 Flash FP8 is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, Ling 3.0 Flash FP8 or Qwen3.6-35B-A3B?

Both models do not have comparable published API token rates, so this page does not name a universal price winner.

Which has the larger context window, Ling 3.0 Flash FP8 or Qwen3.6-35B-A3B?

Both models list the same context window, 262K.

Related comparisons

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Last updated September 18, 2026

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Ling 3.0 Flash FP8 vs Qwen3.6-35B-A3B

Which one for your work

Coding work

Agentic work

Long documents

Chat turn cost

Cache-heavy agent loop cost

Repository review cost

Which one for a specific job

What is actually comparable

Category results, on a stated basis

Instruction following

Agentic

Coding

Reasoning

Knowledge

Math

Multilingual

Multimodal

Shape of the matched evidence

What each workload costs

Chat turn

Repository review

Cache-heavy agent loop

Specification differences

Context window

API model ID

Cached-input rate

Documented inputs

Documented outputs

Provider availability

Reasoning profile

Weight access

License

Release date

Benchmark evidence

Agentic

Coding

Knowledge

Math

Multimodal

Instruction following

Questions

Which is better, Ling 3.0 Flash FP8 or Qwen3.6-35B-A3B?

Which is better for coding, Ling 3.0 Flash FP8 or Qwen3.6-35B-A3B?

Which is better for agentic tasks, Ling 3.0 Flash FP8 or Qwen3.6-35B-A3B?

Which costs less, Ling 3.0 Flash FP8 or Qwen3.6-35B-A3B?

Which has the larger context window, Ling 3.0 Flash FP8 or Qwen3.6-35B-A3B?

Related comparisons

Watch Ling 3.0 Flash FP8 vs Qwen3.6-35B-A3B