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BenchLM

Gemini 3.5 Flash-Lite vs Grok 4.6

Updated September 25, 2026. Rank says Grok 4.6 is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

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Decision reading

Grok 4.6 has the higher public score, 69.19 versus 50.96, and the 90% score intervals do not overlap. 5 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
xAI logo

xAI

69.19/100

Supported · Public rank #15

90% interval 66.3–72.1

Shared results
5
Gemini 3.5 Flash-Lite only
5
Grok 4.6 only
12
Like-for-like categories
3 / 8
Supported: Gemini 3.5 Flash-Lite and Grok 4.6How 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

    Grok 4.6

    Grok 4.6 leads on the public coding lane, 62 to 39.5, with Supported evidence for both models and non-overlapping 90% intervals.

    Confidence: stronger
  • Agentic work

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

    Grok 4.6

    Grok 4.6 leads on the public agentic lane, 67.9 to 30.4, with Supported evidence for both models and non-overlapping 90% intervals.

    Confidence: stronger
  • Long documents

    Prompts that approach the documented context limit

    Gemini 3.5 Flash-Lite

    Gemini 3.5 Flash-Lite has the larger documented context window.

    Confidence: documented
Show secondary and unsupported calls
  • 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. Costs use the listed standard API rates.

    Confidence: listed-rates
  • 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

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-Lite62.0Grok 4.6

Like-for-like · BenchAlign v5.7

Grok 4.6 leads the like-for-like coding row.

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.

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 v5.7 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

Like-for-like
Gemini 3.5 Flash-Lite
30.4
Supported · #66/105
Grok 4.6
67.9
Supported · #8/105
Basis
BenchAlign v5.7 lane · 3 vs 4 public rows
Reading
Grok 4.6 leads

Coding

Like-for-like
Gemini 3.5 Flash-Lite
39.5
Supported · #57/135
Grok 4.6
62.0
Supported · #14/135
Basis
BenchAlign v5.7 lane · 4 vs 8 public rows
Reading
Grok 4.6 leads

Knowledge

Like-for-like
Gemini 3.5 Flash-Lite
49.1
Supported · #60/158
Grok 4.6
69.0
Supported · #13/158
Basis
BenchAlign v5.7 lane · 2 vs 2 public rows
Reading
Grok 4.6 leads

Reasoning

Not comparable
Gemini 3.5 Flash-Lite
61.1
Unranked · 3 rankable rows
Grok 4.6
57.6
#16/19
Basis
Provisional lane · 1 vs 2 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Gemini 3.5 Flash-Lite
76.4
#17/50
Grok 4.6
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Gemini 3.5 Flash-Lite
Not ranked
Grok 4.6
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Gemini 3.5 Flash-Lite
Not ranked
Grok 4.6
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Gemini 3.5 Flash-Lite
Not ranked
Grok 4.6
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
Grok 4.6
$0.005
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
Grok 4.6
$0.118
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
Grok 4.6
$0.2
Fits in one request

Gemini 3.5 Flash-Lite 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.

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

Grok 4.6

$0.5 per 1M cached input tokens

xAI Grok 4.6 release notes

Reasoning profile

Gemini 3.5 Flash-Lite

Reasoning

Grok 4.6

Reasoning

Weight access

Gemini 3.5 Flash-Lite

Proprietary

Grok 4.6

Proprietary

License

Gemini 3.5 Flash-Lite

Proprietary

Grok 4.6

Proprietary

Release date

Gemini 3.5 Flash-Lite

2026-07-21

Grok 4.6

2026-08-12

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
Grok 4.6 has the higher public score, 69.19 versus 50.96, and the 90% score intervals do not overlap.
Workload cost
Repository review: $0.0225 vs $0.118. Cache-heavy agent loop: $0.037 vs $0.2.
Context tradeoff
Gemini 3.5 Flash-Lite has the larger documented window (1M).
Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Gemini 3.5 Flash-Lite or Grok 4.6?

Grok 4.6 has the higher public score, 69.19 versus 50.96, and the 90% score intervals do not overlap. That is the clearest overall quality signal in the current public data.

Which is better for coding, Gemini 3.5 Flash-Lite or Grok 4.6?

Grok 4.6 leads the public coding lane, 62 to 39.5, with Supported evidence for both models and non-overlapping 90% intervals.

Which is better for agentic tasks, Gemini 3.5 Flash-Lite or Grok 4.6?

Grok 4.6 leads the public agentic tasks lane, 67.9 to 30.4, with Supported evidence for both models and non-overlapping 90% intervals.

Which costs less, Gemini 3.5 Flash-Lite or Grok 4.6?

For the stated presets, chat costs $0.00155 on Gemini 3.5 Flash-Lite and $0.005 on Grok 4.6; repository review costs $0.0225 and $0.118; the cache-heavy agent loop costs $0.037 and $0.2. Costs use the listed standard API rates.

Which has the larger context window, Gemini 3.5 Flash-Lite or Grok 4.6?

Gemini 3.5 Flash-Lite has the larger documented context window: 1M, compared with 500K.

Benchmark evidence

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

Browse raw public benchmark evidence22 rows

Agentic

  • Terminal-Bench 2.1

    Gemini 3.5 Flash-Lite54.0%
    Source
    Grok 4.6—

    Not directly comparable

  • OSWorld-Verified

    Gemini 3.5 Flash-Lite74%
    Source
    Grok 4.6—

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Gemini 3.5 Flash-Lite50.2%
    Source
    Grok 4.678.3%
    Source

    Grok 4.6 leads this result

  • Terminal-Bench 3.0

    Gemini 3.5 Flash-Lite—
    Grok 4.626.5%
    Source

    Not directly comparable

  • APEX-Agents

    Gemini 3.5 Flash-Lite—
    Grok 4.657.5%
    Source

    Not directly comparable

  • ApprenticeBench

    Gemini 3.5 Flash-Lite—
    Grok 4.613%
    Source

    Not directly comparable

Coding

  • Terminal-Bench 2.1

    Gemini 3.5 Flash-Lite54.0%
    Source
    Grok 4.6—

    Not directly comparable

  • SWE-bench Pro

    Gemini 3.5 Flash-Lite54.2%
    Source
    Grok 4.6—

    Not directly comparable

  • LiveCodeBench (Vals)

    Gemini 3.5 Flash-Lite79.0%
    Source
    Grok 4.688.2%
    Source

    Grok 4.6 leads this result

  • SWE-bench (Vals)

    Gemini 3.5 Flash-Lite75.0%
    Source
    Grok 4.695.6%
    Source

    Grok 4.6 leads this result

  • Bug Hunt Bench

    Gemini 3.5 Flash-Lite—
    Grok 4.627 fixes
    Source

    Not directly comparable

  • DeepSWE

    Gemini 3.5 Flash-Lite—
    Grok 4.665.9%
    Source

    Not directly comparable

  • cursorBench32

    Gemini 3.5 Flash-Lite—
    Grok 4.670.8%
    Source

    Not directly comparable

  • FrontierCode 1.1 Extended

    Gemini 3.5 Flash-Lite—
    Grok 4.661.3%
    Source

    Not directly comparable

  • VulcanBench v3

    Gemini 3.5 Flash-Lite—
    Grok 4.687.0%
    Source

    Not directly comparable

  • FrontierSWE v2

    Gemini 3.5 Flash-Lite—
    Grok 4.625.3%
    Source

    Not directly comparable

Reasoning

  • MRCRv2

    Gemini 3.5 Flash-Lite72.2%
    Source
    Grok 4.6—

    Not directly comparable

  • ARC-AGI-1

    Gemini 3.5 Flash-Lite—
    Grok 4.687.00%
    Source

    Not directly comparable

  • ARC-AGI-2

    Gemini 3.5 Flash-Lite—
    Grok 4.667.1%
    Source

    Not directly comparable

  • ARC-AGI-3

    Gemini 3.5 Flash-Lite—
    Grok 4.62.1%
    Source

    Not directly comparable

Knowledge

  • GPQA Diamond (Vals)

    Gemini 3.5 Flash-Lite83.8%
    Source
    Grok 4.694.7%
    Source

    Grok 4.6 leads this result

  • MMLU-Pro (Vals)

    Gemini 3.5 Flash-Lite85.8%
    Source
    Grok 4.689.4%
    Source

    Grok 4.6 leads this result

22 public results · 5 shared

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Last updated September 25, 2026