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BenchLM
Google logo
Model A
Gemini 3.5 Flash

Google

64.6/100

Estimated · Public rank #42

90% interval 54.3–74.9

Gemini 3.5 Flash vs Qwen3.8-Flash-Next

Updated August 26, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Alibaba logo
Model B
Qwen3.8-Flash-Next

Alibaba

67.5/100

Estimated · Public rank #25

90% interval 57.7–77.4

Decision reading

Qwen3.8-Flash-Next has the higher public score estimate, 67.54 versus 64.6, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

4 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.

  • Coding work

    Code generation, repair, and software-engineering tasks

    Qwen3.8-Flash-Next

    Qwen3.8-Flash-Next leads on the same 1 weighted benchmark row.

    Confidence: limited

  • Long documents

    Prompts that approach the documented context limit

    Gemini 3.5 Flash

    Gemini 3.5 Flash has the larger documented context window.

    Confidence: documented

Show secondary and unsupported calls

  • 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: 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

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
4
Gemini 3.5 Flash only
18
Qwen3.8-Flash-Next only
20
Like-for-like categories
1 / 8

2 categories use different evidence sets. Those rows remain visible for coverage context but do not name a winner.

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.

Coding

Like-for-like
Gemini 3.5 Flash
55.1
Qwen3.8-Flash-Next
62.5
Weighted basis
1 vs 1 rows
Reading
Qwen3.8-Flash-Next leads

Knowledge

Directional only
Gemini 3.5 Flash
40.2
Qwen3.8-Flash-Next
43.4
Weighted basis
1 vs 2 rows
Reading
Directional only

Multimodal

Directional only
Gemini 3.5 Flash
83.8
Qwen3.8-Flash-Next
90.6
Weighted basis
2 vs 1 rows
Reading
Directional only

Agentic

Not comparable
Gemini 3.5 Flash
77.2
Qwen3.8-Flash-Next
Not measured
Weighted basis
2 vs 0 rows
Reading
Not comparable

Reasoning

Not comparable
Gemini 3.5 Flash
74.7
Qwen3.8-Flash-Next
Not measured
Weighted basis
2 vs 0 rows
Reading
Not comparable

Math

Not comparable
Gemini 3.5 Flash
32.9
Qwen3.8-Flash-Next
Not measured
Weighted basis
2 vs 0 rows
Reading
Not comparable

Multilingual

Not comparable
Gemini 3.5 Flash
Not measured
Qwen3.8-Flash-Next
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
Gemini 3.5 Flash
Not measured
Qwen3.8-Flash-Next
81.3
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

Gemini 3.5 Flash
$0.006
Fits in one request
Qwen3.8-Flash-Next
Self-hosted; infrastructure cost varies
Fits in one request

Qwen3.8-Flash-Next has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Gemini 3.5 Flash
$0.102
Fits in one request
Qwen3.8-Flash-Next
Self-hosted; infrastructure cost varies
Fits in one request

Qwen3.8-Flash-Next has no comparable published API token rate.

Cache-heavy agent loop

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

Gemini 3.5 Flash
$0.15
Fits in one request
Qwen3.8-Flash-Next
Self-hosted; infrastructure cost varies
Fits in one request
Cached-input rate unavailable

Qwen3.8-Flash-Next 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.

Documented inputs

Gemini 3.5 Flash

Not sourced

Qwen3.8-Flash-Next

Not sourced

Documented outputs

Gemini 3.5 Flash

Not sourced

Qwen3.8-Flash-Next

Not sourced

Provider availability

Gemini 3.5 Flash

Not sourced

Qwen3.8-Flash-Next

Not sourced

Reasoning profile

Gemini 3.5 Flash

Reasoning

Qwen3.8-Flash-Next

Reasoning

Weight access

Gemini 3.5 Flash

Proprietary

Qwen3.8-Flash-Next

Open Weight

License

Gemini 3.5 Flash

Proprietary

Qwen3.8-Flash-Next

Open Weight

Release date

Gemini 3.5 Flash

2026-05-19

Qwen3.8-Flash-Next

2026-08-26

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
Qwen3.8-Flash-Next has the higher public score estimate, 67.54 versus 64.6, but the 90% score intervals overlap.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Gemini 3.5 Flash 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 evidence42 rows

Agentic

  • Terminal-Bench 2.0

    Gemini 3.5 Flash76.2%
    Source
    Qwen3.8-Flash-Next—

    Not directly comparable

  • MCP Atlas

    Gemini 3.5 Flash83.6%
    Source
    Qwen3.8-Flash-Next—

    Not directly comparable

  • Toolathlon

    Gemini 3.5 Flash56.5%
    Source
    Qwen3.8-Flash-Next—

    Not directly comparable

  • OSWorld-Verified

    Gemini 3.5 Flash78.4%
    Source
    Qwen3.8-Flash-Next—

    Not directly comparable

  • Finance Agent v2

    Gemini 3.5 Flash57.9%
    Source
    Qwen3.8-Flash-Next—

    Not directly comparable

  • Gert Labs

    Gemini 3.5 Flash61.85%
    Source
    Qwen3.8-Flash-Next—

    Not directly comparable

  • ResearchClawBench

    Gemini 3.5 Flash18.0%
    Source
    Qwen3.8-Flash-Next—

    Not directly comparable

  • CoWorkBench

    Gemini 3.5 Flash—
    Qwen3.8-Flash-Next73.9%
    Source

    Not directly comparable

  • JobBench

    Gemini 3.5 Flash—
    Qwen3.8-Flash-Next55.7%
    Source

    Not directly comparable

  • Agents' Last Exam

    Gemini 3.5 Flash—
    Qwen3.8-Flash-Next51.2%
    Source

    Not directly comparable

  • Toolathlon-Verified

    Gemini 3.5 Flash—
    Qwen3.8-Flash-Next73.5%
    Source

    Not directly comparable

  • AndroidWorld

    Gemini 3.5 Flash—
    Qwen3.8-Flash-Next84.5%
    Source

    Not directly comparable

  • OSWorld 2.0

    Gemini 3.5 Flash—
    Qwen3.8-Flash-Next19.4%
    Source

    Not directly comparable

Coding

  • Terminal-Bench 2.0

    Gemini 3.5 Flash76.2%
    Source
    Qwen3.8-Flash-Next—

    Not directly comparable

  • SWE-bench Pro

    Gemini 3.5 Flash55.1%
    Source
    Qwen3.8-Flash-Next62.5%
    Source

    Qwen3.8-Flash-Next leads this result

  • Vibe Code Bench

    Gemini 3.5 Flash48.68%
    Source
    Qwen3.8-Flash-Next—

    Not directly comparable

  • cursorBench31

    Gemini 3.5 Flash49.8%
    Source
    Qwen3.8-Flash-Next—

    Not directly comparable

  • cursorBench32

    Gemini 3.5 Flash48.8%
    Source
    Qwen3.8-Flash-Next—

    Not directly comparable

  • SWE Multilingual

    Gemini 3.5 Flash—
    Qwen3.8-Flash-Next81%
    Source

    Not directly comparable

  • NL2Repo

    Gemini 3.5 Flash—
    Qwen3.8-Flash-Next48.1%
    Source

    Not directly comparable

  • deepSwe

    Gemini 3.5 Flash—
    Qwen3.8-Flash-Next58.7%
    Source

    Not directly comparable

  • LiveCodeBench v6

    Gemini 3.5 Flash—
    Qwen3.8-Flash-Next91.9%
    Source

    Not directly comparable

Reasoning

  • MRCRv2

    Gemini 3.5 Flash77.3%
    Source
    Qwen3.8-Flash-Next—

    Not directly comparable

  • MRCR 1M

    Gemini 3.5 Flash26.6%
    Source
    Qwen3.8-Flash-Next—

    Not directly comparable

  • ARC-AGI-2

    Gemini 3.5 Flash72.1%
    Source
    Qwen3.8-Flash-Next—

    Not directly comparable

Knowledge

  • GPQA-D

    Gemini 3.5 Flash92.7%
    Source
    Qwen3.8-Flash-Next91.7%
    Source

    Gemini 3.5 Flash leads this result

  • HLE

    Gemini 3.5 Flash40.2%
    Source
    Qwen3.8-Flash-Next35.9%
    Source

    Gemini 3.5 Flash leads this result

  • GPQA

    Gemini 3.5 Flash—
    Qwen3.8-Flash-Next91.7%
    Source

    Not directly comparable

  • HLE w/o tools

    Gemini 3.5 Flash—
    Qwen3.8-Flash-Next35.9%
    Source

    Not directly comparable

Math

  • FrontierMath v2 (Tiers 1-3)

    Gemini 3.5 Flash38.966%
    Source
    Qwen3.8-Flash-Next—

    Not directly comparable

  • FrontierMath v2 (Tier 4)

    Gemini 3.5 Flash14.583%
    Source
    Qwen3.8-Flash-Next—

    Not directly comparable

Multimodal

  • CharXiv

    Gemini 3.5 Flash84.2%
    Source
    Qwen3.8-Flash-Next90.6%
    Source

    Qwen3.8-Flash-Next leads this result

  • MMMU-Pro

    Gemini 3.5 Flash83.6%
    Source
    Qwen3.8-Flash-Next—

    Not directly comparable

  • Blueprint-Bench 2

    Gemini 3.5 Flash33.6%
    Source
    Qwen3.8-Flash-Next—

    Not directly comparable

  • Vision2Web

    Gemini 3.5 Flash—
    Qwen3.8-Flash-Next64.0%
    Source

    Not directly comparable

  • ERQA

    Gemini 3.5 Flash—
    Qwen3.8-Flash-Next72.3%
    Source

    Not directly comparable

  • LVBench

    Gemini 3.5 Flash—
    Qwen3.8-Flash-Next76.6%
    Source

    Not directly comparable

  • RealWorldQA

    Gemini 3.5 Flash—
    Qwen3.8-Flash-Next88.5%
    Source

    Not directly comparable

  • MathVision

    Gemini 3.5 Flash—
    Qwen3.8-Flash-Next90.6%
    Source

    Not directly comparable

  • MathVision w/ Python

    Gemini 3.5 Flash—
    Qwen3.8-Flash-Next95.7%
    Source

    Not directly comparable

  • CharXiv w/o tools

    Gemini 3.5 Flash—
    Qwen3.8-Flash-Next84.6%
    Source

    Not directly comparable

Instruction following

  • IFBench

    Gemini 3.5 Flash—
    Qwen3.8-Flash-Next81.3%
    Source

    Not directly comparable

Frequently asked questions

Which is better, Gemini 3.5 Flash or Qwen3.8-Flash-Next?

Qwen3.8-Flash-Next has the higher public score estimate, 67.54 versus 64.6, 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 Qwen3.8-Flash-Next?

Qwen3.8-Flash-Next leads the like-for-like coding comparison across 1 shared weighted benchmark row.

Which is better for agentic tasks, Gemini 3.5 Flash or Qwen3.8-Flash-Next?

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, Gemini 3.5 Flash or Qwen3.8-Flash-Next?

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, Gemini 3.5 Flash or Qwen3.8-Flash-Next?

Gemini 3.5 Flash has the larger documented context window: 1M, compared with 262K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated August 26, 2026

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