Skip to main content
BenchLM
Data

Gemini 3.5 Flash vs Inkling

Updated October 14, 2026. Rank says Gemini 3.5 Flash is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

Share or export
Share on XLinkedInAPI/MCP

Decision reading

Gemini 3.5 Flash has the higher public score estimate, 61.7 versus 52.13, but the 90% score intervals overlap. Treat that as a lead, not a settled winner. 15 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

61.7/100

Supported · Public rank #46

90% interval 53.5–69.9

Model B
Thinking Machines Lab logo

Thinking Machines Lab

52.13/100

Supported · Public rank #85

90% interval 41.7–62.5

Shared results
15
Gemini 3.5 Flash only
13
Inkling only
9
Like-for-like categories
4 / 8
Supported: Gemini 3.5 Flash and InklingHow 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.

  • Coding work

    Code generation, repair, and software-engineering tasks

    Gemini 3.5 Flash

    Gemini 3.5 Flash has the higher public coding point estimate, 50.4 to 34, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

    Confidence: limited
  • Agentic work

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

    Gemini 3.5 Flash

    Gemini 3.5 Flash has the higher public agentic point estimate, 50.7 to 36.2, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

    Confidence: limited
  • Chat turn cost

    1K fresh input + 500 output tokens

    Inkling

    Inkling has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates
Show secondary and unsupported calls
  • Cache-heavy agent loop cost

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

    Gemini 3.5 Flash

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

    Confidence: listed-rates
  • Repository review cost

    50K fresh input + 3K output tokens

    Gemini 3.5 Flash

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

    Confidence: listed-rates
  • 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.

50.4Gemini 3.5 Flash34.0Inkling

Like-for-like · BenchAlign v5.8

Gemini 3.5 Flash has the higher coding point estimate. Conditional score ranges do not establish rank confidence.

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.

2 categories rest on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.

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.

Bars run 0–100 on each benchmark’s normalized display scale

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign v5.8 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

Like-for-like
Gemini 3.5 Flash
50.7
Supported · #44/124
Inkling
36.2
Supported · #72/124
Basis
BenchAlign v5.8 lane · 8 vs 5 public rows
Reading
Gemini 3.5 Flash leads · intervals overlap

Coding

Like-for-like
Gemini 3.5 Flash
50.4
Supported · #41/149
Inkling
34.0
Supported · #80/149
Basis
BenchAlign v5.8 lane · 7 vs 6 public rows
Reading
Gemini 3.5 Flash leads · intervals overlap

Multimodal

Like-for-like
Gemini 3.5 Flash
87.8
#7/54
Inkling
67.5
#35/54
Basis
Provisional lane · 2 vs 2 weighted rows
Reading
Gemini 3.5 Flash leads

Knowledge

Like-for-like
Gemini 3.5 Flash
65.3
Supported · #32/181
Inkling
54.5
Supported · #62/181
Basis
BenchAlign v5.8 lane · 4 vs 6 public rows
Reading
Gemini 3.5 Flash leads · intervals overlap

Reasoning

Directional only
Gemini 3.5 Flash
70.9
#19/29
Inkling
79.0
#14/29
Basis
Provisional lane · 2 vs 0 weighted rows
Reading
Directional only

Instruction following

Directional only
Gemini 3.5 Flash
87.4
#36/128
Inkling
87.6
#35/128
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Directional only

Multilingual

Not comparable
Gemini 3.5 Flash
Not ranked
Inkling
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Gemini 3.5 Flash
67.1
Unranked · 2 rankable rows
Inkling
58.3
#11/12
Basis
Provisional lane · 2 vs 3 weighted rows
Reading
Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.8) 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
$0.006
Fits in one request
Inkling
$0.00421
Fits in one request

Inkling has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Gemini 3.5 Flash
$0.102
Fits in one request
Inkling
$0.10754
Fits in one request

Gemini 3.5 Flash 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
$0.15
Fits in one request
Inkling
$0.159
Fits in one request

Gemini 3.5 Flash has the lower modeled cost

Costs use the listed standard API rates.

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.

Context window

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

Gemini 3.5 Flash

Inkling

1M

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

$0.15 per 1M cached input tokens

Google Gemini API pricing

Inkling

$0.374 per 1M cached input tokens

Documented inputs

Gemini 3.5 Flash

Not sourced

Inkling

Not sourced

Documented outputs

Gemini 3.5 Flash

Not sourced

Inkling

Not sourced

Provider availability

Gemini 3.5 Flash

Not sourced

Inkling

Not sourced

Reasoning profile

Gemini 3.5 Flash

Reasoning

Inkling

Hybrid

Weight access

Gemini 3.5 Flash

Proprietary

Inkling

Open Weight

License

Gemini 3.5 Flash

Proprietary

Inkling

Open Weight

Release date

Gemini 3.5 Flash

2026-05-19

Inkling

2026-07-15

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
Gemini 3.5 Flash has the higher public score estimate, 61.7 versus 52.13, but the 90% score intervals overlap.
Workload cost
Repository review: $0.102 vs $0.10754. Cache-heavy agent loop: $0.15 vs $0.159.
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 or Inkling?

Gemini 3.5 Flash has the higher public score estimate, 61.7 versus 52.13, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, Gemini 3.5 Flash or Inkling?

Gemini 3.5 Flash has the higher public coding point estimate, 50.4 to 34, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

Which is better for agentic tasks, Gemini 3.5 Flash or Inkling?

Gemini 3.5 Flash has the higher public agentic tasks point estimate, 50.7 to 36.2, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

Which costs less, Gemini 3.5 Flash or Inkling?

For the stated presets, chat costs $0.006 on Gemini 3.5 Flash and $0.00421 on Inkling; repository review costs $0.102 and $0.10754; the cache-heavy agent loop costs $0.15 and $0.159. Costs use the listed standard API rates.

Which has the larger context window, Gemini 3.5 Flash or Inkling?

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 evidence37 rows

Agentic

  • Terminal-Bench 2.1

    Gemini 3.5 Flash76.2%
    Source
    Inkling63.8%
    Source

    Gemini 3.5 Flash leads this result

  • MCP Atlas

    Gemini 3.5 Flash83.6%
    Source
    Inkling74.1%
    Source

    Gemini 3.5 Flash leads this result

  • Toolathlon

    Gemini 3.5 Flash56.5%
    Source
    Inkling—

    Not directly comparable

  • OSWorld-Verified

    Gemini 3.5 Flash78.4%
    Source
    Inkling—

    Not directly comparable

  • Finance Agent v2

    Gemini 3.5 Flash57.9%
    Source
    Inkling—

    Not directly comparable

  • Gert Labs

    Gemini 3.5 Flash61.85%
    Source
    Inkling—

    Not directly comparable

  • ResearchClawBench

    Gemini 3.5 Flash18.0%
    Source
    Inkling—

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Gemini 3.5 Flash74.2%
    Source
    Inkling47.6%
    Source

    Gemini 3.5 Flash leads this result

  • BrowseComp

    Gemini 3.5 Flash—
    Inkling77.1%
    Source

    Not directly comparable

  • CWE-bench v1

    Gemini 3.5 Flash—
    Inkling37.0%
    Source

    Not directly comparable

Coding

  • Terminal-Bench 2.1

    Gemini 3.5 Flash76.2%
    Source
    Inkling63.8%
    Source

    Gemini 3.5 Flash leads this result

  • SWE-bench Pro

    Gemini 3.5 Flash55.1%
    Source
    Inkling54.3%
    Source

    Gemini 3.5 Flash leads this result

  • Vibe Code Bench

    Gemini 3.5 Flash48.68%
    Source
    Inkling—

    Not directly comparable

  • cursorBench31

    Gemini 3.5 Flash49.8%
    Source
    Inkling—

    Not directly comparable

  • CursorBench 3.2

    Gemini 3.5 Flash48.8%
    Source
    Inkling—

    Not directly comparable

  • LiveCodeBench (Vals)

    Gemini 3.5 Flash87.6%
    Source
    Inkling85.5%
    Source

    Gemini 3.5 Flash leads this result

  • SWE-bench (Vals)

    Gemini 3.5 Flash78.8%
    Source
    Inkling77.6%
    Source

    Gemini 3.5 Flash leads this result

  • SWE-bench Verified

    Gemini 3.5 Flash—
    Inkling77.6%
    Source

    Not directly comparable

  • FrontierSWE v2

    Gemini 3.5 Flash—
    Inkling4.1%
    Source

    Not directly comparable

Reasoning

  • MRCRv2

    Gemini 3.5 Flash77.3%
    Source
    Inkling—

    Not directly comparable

  • MRCR 1M

    Gemini 3.5 Flash26.6%
    Source
    Inkling—

    Not directly comparable

  • ARC-AGI-2

    Gemini 3.5 Flash72.1%
    Source
    Inkling—

    Not directly comparable

  • ARC-AGI-1

    Gemini 3.5 Flash92.50%
    Source
    Inkling—

    Not directly comparable

Multimodal

  • CharXiv

    Gemini 3.5 Flash84.2%
    Source
    Inkling82%
    Source

    Gemini 3.5 Flash leads this result

  • MMMU-Pro

    Gemini 3.5 Flash83.6%
    Source
    Inkling73.5%
    Source

    Gemini 3.5 Flash leads this result

  • Blueprint-Bench 2

    Gemini 3.5 Flash33.6%
    Source
    Inkling—

    Not directly comparable

  • CharXiv w/o tools

    Gemini 3.5 Flash—
    Inkling78.1%
    Source

    Not directly comparable

Knowledge

  • GPQA-D

    Gemini 3.5 Flash92.7%
    Source
    Inkling87.9%
    Source

    Gemini 3.5 Flash leads this result

  • HLE

    Gemini 3.5 Flash40.2%
    Source
    Inkling46%
    Source

    Inkling leads this result

  • GPQA Diamond (Vals)

    Gemini 3.5 Flash92.7%
    Source
    Inkling87.1%
    Source

    Gemini 3.5 Flash leads this result

  • MMLU-Pro (Vals)

    Gemini 3.5 Flash89.5%
    Source
    Inkling86.3%
    Source

    Gemini 3.5 Flash leads this result

  • GPQA

    Gemini 3.5 Flash—
    Inkling87.9%
    Source

    Not directly comparable

  • HLE w/o tools

    Gemini 3.5 Flash—
    Inkling30%
    Source

    Not directly comparable

Instruction following

  • IFBench

    Gemini 3.5 Flash—
    Inkling79.8%
    Source

    Not directly comparable

Math

  • FrontierMath v2 (Tiers 1-3)

    Shared source
    Gemini 3.5 Flash62.807%
    Inkling33.333%

    Gemini 3.5 Flash leads this result

  • FrontierMath v2 (Tier 4)

    Shared source
    Gemini 3.5 Flash26.829%
    Inkling4.878%

    Gemini 3.5 Flash leads this result

  • AIME26

    Gemini 3.5 Flash—
    Inkling97.1%
    Source

    Not directly comparable

37 public results · 15 shared

Watch Gemini 3.5 Flash vs Inkling

One weekly email when material rank, price, or benchmark evidence changes make this matchup worth revisiting.

Read a sample issue

Join 5,500+ readers.

Last updated October 14, 2026