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Model comparison

Interfaze Beta vs Ling 3.0 Flash FP8

Updated August 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Interfaze Beta

Interfaze

Evidence status unavailable

90% interval unavailable

Ling 3.0 Flash FP8

InclusionAI

Evidence status unavailable

90% interval unavailable

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

2 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.

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.

  • Long documents

    Prompts that approach the documented context limit

    Interfaze Beta

    Interfaze Beta has the larger documented context window.

    Confidence: documented

Show secondary and unsupported calls
  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    No shared weighted benchmark basis supports a winner.

    Confidence: limited

  • Agentic work

    Tool use, computer use, and multi-step task completion

    Not enough matched evidence

    No shared weighted benchmark basis supports a winner.

    Confidence: limited

  • 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: rate-fallback

  • 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

What is actually comparable

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

Shared results
2
Interfaze Beta only
7
Ling 3.0 Flash FP8 only
2
Like-for-like categories
1 / 8

Category results, on a stated basis

Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.

Knowledge

Like-for-like
Interfaze Beta
89.9
Ling 3.0 Flash FP8
84.0
Weighted basis
1 vs 1 rows
Reading
Interfaze Beta leads

Agentic

Not comparable
Interfaze Beta
Not measured
Ling 3.0 Flash FP8
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Coding

Not comparable
Interfaze Beta
Not measured
Ling 3.0 Flash FP8
40.4
Weighted basis
0 vs 1 rows
Reading
Not comparable

Reasoning

Not comparable
Interfaze Beta
Not measured
Ling 3.0 Flash FP8
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Math

Not comparable
Interfaze Beta
Not measured
Ling 3.0 Flash FP8
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multilingual

Not comparable
Interfaze Beta
Not measured
Ling 3.0 Flash FP8
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multimodal

Not comparable
Interfaze Beta
71.1
Ling 3.0 Flash FP8
Not measured
Weighted basis
1 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
Interfaze Beta
Not measured
Ling 3.0 Flash FP8
73.4
Weighted basis
0 vs 1 rows
Reading
Not comparable

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.

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

Interfaze Beta
$0.00325
Fits in one request
Ling 3.0 Flash FP8
API rate not published
Fits in one request

Ling 3.0 Flash FP8 has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Interfaze Beta
$0.0855
Fits in one request
Ling 3.0 Flash FP8
API rate not published
Fits in one request

Ling 3.0 Flash FP8 has no comparable published API token rate.

Cache-heavy agent loop

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

Interfaze Beta
$0.365
Fits in one request
Cached input priced at the published list-input rate
Ling 3.0 Flash FP8
API rate not published
Fits in one request
Cached-input rate unavailable

Interfaze Beta has no published cached-input rate, so cached tokens use its listed input rate. Ling 3.0 Flash FP8 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.

API model ID

Interfaze Beta

Not sourced

Ling 3.0 Flash FP8

Not sourced

Cached-input rate

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

Interfaze Beta

Not published

Ling 3.0 Flash FP8

No comparable hosted API rate

InclusionAI Ling 3.0 Flash FP8 model card

Documented inputs

Interfaze Beta

Not sourced

Ling 3.0 Flash FP8

Not sourced

Documented outputs

Interfaze Beta

Not sourced

Ling 3.0 Flash FP8

Not sourced

Provider availability

Interfaze Beta

Not sourced

Ling 3.0 Flash FP8

Not sourced

Reasoning profile

Interfaze Beta

Reasoning

Ling 3.0 Flash FP8

Reasoning

Weight access

Interfaze Beta

Proprietary

Ling 3.0 Flash FP8

Open Weight

License

Interfaze Beta

Proprietary

Ling 3.0 Flash FP8

Open Weight

Release date

Interfaze Beta

2026-05-11

Ling 3.0 Flash FP8

2026-08-04

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
Interfaze Beta has the larger documented window (1M).

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 evidence11 rows

Coding

  • Spider 2.0-Lite

    Interfaze Beta52.9%
    Source
    Ling 3.0 Flash FP8

    Not directly comparable

  • SciCode

    Interfaze Beta
    Ling 3.0 Flash FP840.4%
    Source

    Not directly comparable

Knowledge

  • GPQA

    Interfaze Beta89.9%
    Source
    Ling 3.0 Flash FP884%
    Source

    Interfaze Beta leads this result

  • GPQA-D

    Interfaze Beta89.9%
    Source
    Ling 3.0 Flash FP884.0%
    Source

    Interfaze Beta leads this result

  • MMMLU

    Interfaze Beta90.9%
    Source
    Ling 3.0 Flash FP8

    Not directly comparable

Multimodal

  • OCRBench V2

    Interfaze Beta70.7%
    Source
    Ling 3.0 Flash FP8

    Not directly comparable

  • olmOCR

    Interfaze Beta85.7%
    Source
    Ling 3.0 Flash FP8

    Not directly comparable

  • RefCOCO (avg)

    Interfaze Beta82.1%
    Source
    Ling 3.0 Flash FP8

    Not directly comparable

  • MMMU-Pro

    Interfaze Beta71.1%
    Source
    Ling 3.0 Flash FP8

    Not directly comparable

Instruction following

  • SOB Value Acc

    Interfaze Beta79.5%
    Source
    Ling 3.0 Flash FP8

    Not directly comparable

  • IFBench

    Interfaze Beta
    Ling 3.0 Flash FP873.4%
    Source

    Not directly comparable

Frequently asked questions

Which is better, Interfaze Beta or Ling 3.0 Flash FP8?

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, Interfaze Beta or Ling 3.0 Flash FP8?

The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.

Which is better for agentic tasks, Interfaze Beta or Ling 3.0 Flash FP8?

The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.

Which costs less, Interfaze Beta or Ling 3.0 Flash FP8?

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, Interfaze Beta or Ling 3.0 Flash FP8?

Interfaze Beta has the larger documented context window: 1M, compared with 262K.

Related comparisons

Last updated August 4, 2026

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