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BenchLM

Gemini 3.5 Flash-Lite vs Interfaze Beta

Updated September 24, 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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Decision reading

The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. Use the documented cost, context, and runtime rows instead. 0 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A
Google logo

Google

50.96/100

Supported · Public rank #70

90% interval 39.0–63.0

Model B
Interfaze logo

Interfaze

—

Evidence status unavailable

90% interval unavailable

Shared results
0
Gemini 3.5 Flash-Lite only
10
Interfaze Beta only
9
Like-for-like categories
0 / 8
Supported: Gemini 3.5 Flash-LiteHow the comparison works

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.

  • Chat turn cost

    1K fresh input + 500 output tokens

    Gemini 3.5 Flash-Lite

    Gemini 3.5 Flash-Lite has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates
  • Cache-heavy agent loop cost

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

    Gemini 3.5 Flash-Lite

    Gemini 3.5 Flash-Lite has the lower estimated token cost for this stated workload. Interfaze Beta has no published cached-input rate, so cached tokens use its listed input rate.

    Confidence: rate-fallback
Show secondary and unsupported calls
  • Repository review cost

    50K fresh input + 3K output tokens

    Gemini 3.5 Flash-Lite

    Gemini 3.5 Flash-Lite has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates
  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    Interfaze Beta 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

    Interfaze Beta 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

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.

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

39.5Gemini 3.5 Flash-Lite—Interfaze Beta

Not comparable · BenchAlign v5.7

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.

Same basis rules as the category table below

What is actually comparable

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

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.

A shared-evidence shape is not available.

BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign v5.7 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.

Agentic

Not comparable
Gemini 3.5 Flash-Lite
30.4
Supported · #66/105
Interfaze Beta
Not ranked
Basis
BenchAlign v5.7 lane · 3 vs 0 public rows
Reading
Not comparable

Coding

Not comparable
Gemini 3.5 Flash-Lite
39.5
Supported · #57/135
Interfaze Beta
Not ranked
Basis
BenchAlign v5.7 lane · 4 vs 1 public rows
Reading
Not comparable

Reasoning

Not comparable
Gemini 3.5 Flash-Lite
61.1
Unranked · 3 rankable rows
Interfaze Beta
Not ranked
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Gemini 3.5 Flash-Lite
76.4
#17/50
Interfaze Beta
27.6
Unranked · 5 rankable rows
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Not comparable

Knowledge

Not comparable
Gemini 3.5 Flash-Lite
49.1
Supported · #60/158
Interfaze Beta
Not ranked
Basis
BenchAlign v5.7 lane · 2 vs 3 public rows
Reading
Not comparable

Multilingual

Not comparable
Gemini 3.5 Flash-Lite
Not ranked
Interfaze Beta
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Gemini 3.5 Flash-Lite
Not ranked
Interfaze Beta
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Gemini 3.5 Flash-Lite
Not ranked
Interfaze Beta
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.7) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

Supported evidence per lane · bars run 0–100Methodology

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

Gemini 3.5 Flash-Lite
$0.00155
Fits in one request
Interfaze Beta
$0.00325
Fits in one request

Gemini 3.5 Flash-Lite has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Gemini 3.5 Flash-Lite
$0.0225
Fits in one request
Interfaze Beta
$0.0855
Fits in one request

Gemini 3.5 Flash-Lite has the lower modeled cost

Costs use the listed standard API rates.

Cache-heavy agent loop

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

Gemini 3.5 Flash-Lite
$0.037
Fits in one request
Interfaze Beta
$0.365
Fits in one request
Cached input priced at the published list-input rate

Gemini 3.5 Flash-Lite has the lower modeled cost

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

Cached input falls back to the list input rate only where a cached rate is unpublished

Specification differences

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

Cached-input rate

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

Gemini 3.5 Flash-Lite

$0.03 per 1M cached input tokens

Google Gemini API pricing

Interfaze Beta

Not published

Reasoning profile

Gemini 3.5 Flash-Lite

Reasoning

Interfaze Beta

Reasoning

Weight access

Gemini 3.5 Flash-Lite

Proprietary

Interfaze Beta

Proprietary

License

Gemini 3.5 Flash-Lite

Proprietary

Interfaze Beta

Proprietary

Release date

Gemini 3.5 Flash-Lite

2026-07-21

Interfaze Beta

2026-05-11

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
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict.
Workload cost
Repository review: $0.0225 vs $0.0855. Cache-heavy agent loop: $0.037 vs $0.365.
Context tradeoff
Both models list 1M.
Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Gemini 3.5 Flash-Lite or Interfaze Beta?

The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Gemini 3.5 Flash-Lite or Interfaze Beta?

Interfaze Beta is not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, Gemini 3.5 Flash-Lite or Interfaze Beta?

Interfaze Beta is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, Gemini 3.5 Flash-Lite or Interfaze Beta?

For the stated presets, chat costs $0.00155 on Gemini 3.5 Flash-Lite and $0.00325 on Interfaze Beta; repository review costs $0.0225 and $0.0855; the cache-heavy agent loop costs $0.037 and $0.365. Interfaze Beta has no published cached-input rate, so cached tokens use its listed input rate.

Which has the larger context window, Gemini 3.5 Flash-Lite or Interfaze Beta?

Both models list the same context window, 1M.

Benchmark evidence

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

Browse raw public benchmark evidence19 rows

Agentic

  • Terminal-Bench 2.1

    Gemini 3.5 Flash-Lite54.0%
    Source
    Interfaze Beta—

    Not directly comparable

  • OSWorld-Verified

    Gemini 3.5 Flash-Lite74%
    Source
    Interfaze Beta—

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Gemini 3.5 Flash-Lite50.2%
    Source
    Interfaze Beta—

    Not directly comparable

Coding

  • Terminal-Bench 2.1

    Gemini 3.5 Flash-Lite54.0%
    Source
    Interfaze Beta—

    Not directly comparable

  • SWE-bench Pro

    Gemini 3.5 Flash-Lite54.2%
    Source
    Interfaze Beta—

    Not directly comparable

  • LiveCodeBench (Vals)

    Gemini 3.5 Flash-Lite79.0%
    Source
    Interfaze Beta—

    Not directly comparable

  • SWE-bench (Vals)

    Gemini 3.5 Flash-Lite75.0%
    Source
    Interfaze Beta—

    Not directly comparable

  • Spider 2.0-Lite

    Gemini 3.5 Flash-Lite—
    Interfaze Beta52.9%
    Source

    Not directly comparable

Reasoning

  • MRCRv2

    Gemini 3.5 Flash-Lite72.2%
    Source
    Interfaze Beta—

    Not directly comparable

Multimodal

  • OCRBench V2

    Gemini 3.5 Flash-Lite—
    Interfaze Beta70.7%
    Source

    Not directly comparable

  • olmOCR

    Gemini 3.5 Flash-Lite—
    Interfaze Beta85.7%
    Source

    Not directly comparable

  • RefCOCO (avg)

    Gemini 3.5 Flash-Lite—
    Interfaze Beta82.1%
    Source

    Not directly comparable

  • MMMU-Pro

    Gemini 3.5 Flash-Lite—
    Interfaze Beta71.1%
    Source

    Not directly comparable

Knowledge

  • GPQA Diamond (Vals)

    Gemini 3.5 Flash-Lite83.8%
    Source
    Interfaze Beta—

    Not directly comparable

  • MMLU-Pro (Vals)

    Gemini 3.5 Flash-Lite85.8%
    Source
    Interfaze Beta—

    Not directly comparable

  • GPQA

    Gemini 3.5 Flash-Lite—
    Interfaze Beta89.9%
    Source

    Not directly comparable

  • GPQA-D

    Gemini 3.5 Flash-Lite—
    Interfaze Beta89.9%
    Source

    Not directly comparable

  • MMMLU

    Gemini 3.5 Flash-Lite—
    Interfaze Beta90.9%
    Source

    Not directly comparable

Instruction following

  • SOB Value Acc

    Gemini 3.5 Flash-Lite—
    Interfaze Beta79.5%
    Source

    Not directly comparable

19 public results · 0 shared

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Last updated September 24, 2026