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Exaone 4.0 32B vs Qwen3.5-122B-A10B

Updated September 27, 2026. Rank says Qwen3.5-122B-A10B is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

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Decision reading

Qwen3.5-122B-A10B has the higher public score estimate, 40.06 versus 31.22, but the 90% score intervals overlap. Treat that as a lead, not a settled winner. 1 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A
LG AI Research logo

LG AI Research

31.22/100

Estimated · Public rank #150

90% interval 19.7–42.7

Model B
Alibaba logo

Alibaba

40.06/100

Estimated · Public rank #113

90% interval 19.5–60.6

Shared results
1
Exaone 4.0 32B only
1
Qwen3.5-122B-A10B only
14
Like-for-like categories
1 / 8
Estimated: Exaone 4.0 32B and Qwen3.5-122B-A10BHow 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.

  • Long documents

    Prompts that approach the documented context limit

    Qwen3.5-122B-A10B

    Qwen3.5-122B-A10B 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

    Exaone 4.0 32B 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

    Exaone 4.0 32B is not ranked on the public lane for agentic, so no winner is named for agentic.

    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

    The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. Exaone 4.0 32B does not fit this workload in one request. Exaone 4.0 32B has no comparable published API token rate. Qwen3.5-122B-A10B has no comparable published API token rate.

    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

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.

—Exaone 4.0 32B35.7Qwen3.5-122B-A10B

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.

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.

Knowledge

Like-for-like
Exaone 4.0 32B
29.0
Supported · #138/158
Qwen3.5-122B-A10B
41.5
Supported · #86/158
Basis
BenchAlign v5.7 lane · 1 vs 3 public rows
Reading
Qwen3.5-122B-A10B leads · intervals overlap

Agentic

Not comparable
Exaone 4.0 32B
Not ranked
Qwen3.5-122B-A10B
23.1
Estimated · #84/105
Basis
BenchAlign v5.7 lane · 0 vs 3 public rows
Reading
Not comparable

Coding

Not comparable
Exaone 4.0 32B
Not ranked
Qwen3.5-122B-A10B
35.7
Supported · #73/135
Basis
BenchAlign v5.7 lane · 0 vs 1 public rows
Reading
Not comparable

Reasoning

Not comparable
Exaone 4.0 32B
Not ranked
Qwen3.5-122B-A10B
49.8
Unranked · 3 rankable rows
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Exaone 4.0 32B
Not ranked
Qwen3.5-122B-A10B
57.0
#34/50
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Exaone 4.0 32B
Not ranked
Qwen3.5-122B-A10B
36.8
#10/12
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Exaone 4.0 32B
36.5
Unranked · 1 rankable row
Qwen3.5-122B-A10B
91.6
#11/124
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Exaone 4.0 32B
Not ranked
Qwen3.5-122B-A10B
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

Exaone 4.0 32B
API rate not published
Fits in one request
Qwen3.5-122B-A10B
Self-hosted; infrastructure cost varies
Fits in one request

Exaone 4.0 32B has no comparable published API token rate. Qwen3.5-122B-A10B has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Exaone 4.0 32B
API rate not published
Fits in one request
Qwen3.5-122B-A10B
Self-hosted; infrastructure cost varies
Fits in one request

Exaone 4.0 32B has no comparable published API token rate. Qwen3.5-122B-A10B has no comparable published API token rate.

Cache-heavy agent loop

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

Exaone 4.0 32B
API rate not published
Does not fit in one request
Cached-input rate unavailable
Qwen3.5-122B-A10B
Self-hosted; infrastructure cost varies
Fits in one request
Cached-input rate unavailable

Exaone 4.0 32B does not fit this workload in one request. Exaone 4.0 32B has no comparable published API token rate. Qwen3.5-122B-A10B has no comparable published API token 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.

Context window

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

Exaone 4.0 32B

128K

Qwen3.5-122B-A10B

262K

API model ID

Exaone 4.0 32B

Not sourced

Qwen3.5-122B-A10B

Not sourced

Cached-input rate

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

Exaone 4.0 32B

No comparable hosted API rate

Qwen3.5-122B-A10B

No comparable hosted API rate

Documented inputs

Exaone 4.0 32B

Not sourced

Qwen3.5-122B-A10B

Not sourced

Documented outputs

Exaone 4.0 32B

Not sourced

Qwen3.5-122B-A10B

Not sourced

Provider availability

Exaone 4.0 32B

Not sourced

Qwen3.5-122B-A10B

Not sourced

Reasoning profile

Exaone 4.0 32B

Reasoning

Qwen3.5-122B-A10B

Reasoning

Weight access

Exaone 4.0 32B

Open Weight

Qwen3.5-122B-A10B

Open Weight

License

Exaone 4.0 32B

Open Weight

Qwen3.5-122B-A10B

Open Weight

Release date

Exaone 4.0 32B

Not sourced

Qwen3.5-122B-A10B

2026-03-04

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
Qwen3.5-122B-A10B has the higher public score estimate, 40.06 versus 31.22, but the 90% score intervals overlap.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Qwen3.5-122B-A10B has the larger documented window (262K).
Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Exaone 4.0 32B or Qwen3.5-122B-A10B?

Qwen3.5-122B-A10B has the higher public score estimate, 40.06 versus 31.22, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, Exaone 4.0 32B or Qwen3.5-122B-A10B?

Exaone 4.0 32B is not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, Exaone 4.0 32B or Qwen3.5-122B-A10B?

Exaone 4.0 32B is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, Exaone 4.0 32B or Qwen3.5-122B-A10B?

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, Exaone 4.0 32B or Qwen3.5-122B-A10B?

Qwen3.5-122B-A10B has the larger documented context window: 262K, compared with 128K.

Benchmark evidence

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

Browse raw public benchmark evidence16 rows

Agentic

  • Terminal-Bench 2.0

    Exaone 4.0 32B—
    Qwen3.5-122B-A10B49.4%
    Source

    Not directly comparable

  • BrowseComp

    Exaone 4.0 32B—
    Qwen3.5-122B-A10B63.8%
    Source

    Not directly comparable

  • OSWorld-Verified

    Exaone 4.0 32B—
    Qwen3.5-122B-A10B58%
    Source

    Not directly comparable

Coding

  • SWE-bench Verified

    Exaone 4.0 32B—
    Qwen3.5-122B-A10B72%
    Source

    Not directly comparable

Reasoning

  • LongBench v2

    Exaone 4.0 32B—
    Qwen3.5-122B-A10B60.2%
    Source

    Not directly comparable

Multimodal

  • MMMU

    Exaone 4.0 32B—
    Qwen3.5-122B-A10B83.9%
    Source

    Not directly comparable

  • MMVU

    Exaone 4.0 32B—
    Qwen3.5-122B-A10B74.7%
    Source

    Not directly comparable

  • MathVision

    Exaone 4.0 32B—
    Qwen3.5-122B-A10B86.2%
    Source

    Not directly comparable

  • CharXiv

    Exaone 4.0 32B—
    Qwen3.5-122B-A10B77.2%
    Source

    Not directly comparable

  • V*

    Exaone 4.0 32B—
    Qwen3.5-122B-A10B93.2%
    Source

    Not directly comparable

Knowledge

  • MMLU-Pro

    Exaone 4.0 32B81.8%
    Source
    Qwen3.5-122B-A10B86.7%
    Source

    Qwen3.5-122B-A10B leads this result

  • SuperGPQA

    Exaone 4.0 32B—
    Qwen3.5-122B-A10B67.1%
    Source

    Not directly comparable

  • GPQA

    Exaone 4.0 32B—
    Qwen3.5-122B-A10B86.6%
    Source

    Not directly comparable

Multilingual

  • MMLU-ProX

    Exaone 4.0 32B—
    Qwen3.5-122B-A10B82.2%
    Source

    Not directly comparable

Instruction following

  • IFEval

    Exaone 4.0 32B—
    Qwen3.5-122B-A10B93.4%
    Source

    Not directly comparable

Math

  • AIME 2025

    Exaone 4.0 32B85.3%
    Source
    Qwen3.5-122B-A10B—

    Not directly comparable

16 public results · 1 shared

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Last updated September 27, 2026