Gemini 4 Argon vs Qwen3.5 Plus

Updated November 13, 2026. Rank says Gemini 4 Argon is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

Decision reading

Gemini 4 Argon has the higher public point estimate, 79.03 versus 49.06. Their conditional score ranges do not overlap. These ranges do not establish rank confidence. 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

Gemini 4 Argon

Google

79.03/100

Supported · Public rank #8

90% interval 75.4–82.7

Model B

Qwen3.5 Plus

Alibaba

49.06/100

Estimated · Public rank #111

Conditional range 34.7–63.4

API price per 1M tokens

Gemini 4 Argon: $2 input / $10 output

Qwen3.5 Plus: $0.40 input / $2.40 output

Context window

Gemini 4 Argon: 1M

Qwen3.5 Plus: 1M

Released

Gemini 4 Argon: September 30, 2026

Qwen3.5 Plus: March 4, 2026

Shared results: 1
Gemini 4 Argon only: 38
Qwen3.5 Plus only: 1
Like-for-like categories: 0 / 8

Supported: Gemini 4 Argon · Estimated: Qwen3.5 Plus. Conditional ranges do not establish rank confidence.How 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
Qwen3.5 Plus
Qwen3.5 Plus 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
Qwen3.5 Plus
Qwen3.5 Plus has the lower estimated token cost for this stated workload. Qwen3.5 Plus 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
Qwen3.5 Plus
Qwen3.5 Plus 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
Qwen3.5 Plus 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
Qwen3.5 Plus 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.

Pick the job you would use them for

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

71.8Gemini 4 Argon—Qwen3.5 Plus

Not comparable · BenchAlign v5.8

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.

Open the coding leaderboard Shortlist models for this job

Same basis rules as the category table below

Or describe your own job

The LLM Selector reads what you need a model for and returns a shortlist, ranked in the same order the job pages publish.

What do you need a model for?

Describe the task and constraints. This selector recommends models; it cannot carry out the task or access your files and accounts.

We keep what you type here, drafts included, for 180 days, and after that only the job and requirements read from it. Nothing is tied to your IP address or account. Leave out names and other personal details. Privacy

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 v5.8 lane for agentic, coding, reasoning, multimodal, 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 4 Argon: 74.9; Supported · #6/135
Qwen3.5 Plus: Not ranked
Basis: BenchAlign v5.8 lane · 13 vs 1 public rows
Reading: Not comparable

Coding

Not comparable

Gemini 4 Argon: 71.8; Supported · #9/162
Qwen3.5 Plus: Not ranked
Basis: BenchAlign v5.8 lane · 9 vs 1 public rows
Reading: Not comparable

Reasoning

Not comparable

Gemini 4 Argon: 76.5; Supported · #7/160
Qwen3.5 Plus: Not ranked
Basis: BenchAlign v5.8 lane · 7 vs 0 public rows
Reading: Not comparable

Multimodal

Not comparable

Gemini 4 Argon: Not ranked
Qwen3.5 Plus: Not ranked
Basis: BenchAlign v5.8 lane · 5 vs 0 public rows
Reading: Not comparable

Knowledge

Not comparable

Gemini 4 Argon: 79.2; Supported · #8/180
Qwen3.5 Plus: Not ranked
Basis: BenchAlign v5.8 lane · 2 vs 0 public rows
Reading: Not comparable

Multilingual

Not comparable

Gemini 4 Argon: Not ranked
Qwen3.5 Plus: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Instruction following

Not comparable

Gemini 4 Argon: Not ranked
Qwen3.5 Plus: Not ranked
Basis: Provisional lane · 0 vs 0 weighted rows
Reading: Not comparable

Math

Not comparable

Gemini 4 Argon: 87.4; Unranked · 2 rankable rows
Qwen3.5 Plus: Not ranked
Basis: Provisional lane · 2 vs 0 weighted rows
Reading: Not comparable

Category scores with the server-provided evidence basis for Gemini 4 Argon and Qwen3.5 Plus
Category	Gemini 4 Argon	Qwen3.5 Plus	Basis	Reading
Agentic	74.9Supported · #6/135	Not ranked	Not comparableBenchAlign v5.8 lane · 13 vs 1 public rows	Not comparable
Coding	71.8Supported · #9/162	Not ranked	Not comparableBenchAlign v5.8 lane · 9 vs 1 public rows	Not comparable
Reasoning	76.5Supported · #7/160	Not ranked	Not comparableBenchAlign v5.8 lane · 7 vs 0 public rows	Not comparable
Multimodal	Not ranked	Not ranked	Not comparableBenchAlign v5.8 lane · 5 vs 0 public rows	Not comparable
Knowledge	79.2Supported · #8/180	Not ranked	Not comparableBenchAlign v5.8 lane · 2 vs 0 public rows	Not comparable
Multilingual	Not ranked	Not ranked	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable
Instruction following	Not ranked	Not ranked	Not comparableProvisional lane · 0 vs 0 weighted rows	Not comparable
Math	87.4Unranked · 2 rankable rows	Not ranked	Not comparableProvisional lane · 2 vs 0 weighted rows	Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, reasoning, multimodal, 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 4 Argon: $0.007; Fits in one request
Qwen3.5 Plus: $0.0016; Fits in one request

Qwen3.5 Plus has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Gemini 4 Argon: $0.13; Fits in one request
Qwen3.5 Plus: $0.0272; Fits in one request

Qwen3.5 Plus 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 4 Argon: $0.16; Fits in one request
Qwen3.5 Plus: $0.112; Fits in one request; Cached input priced at the published list-input rate

Qwen3.5 Plus has the lower modeled cost

Qwen3.5 Plus has no published cached-input rate, so cached tokens use its listed input rate.

Your workload

Enter a month of tokens to price it at both models’ listed API rates.

Input, millionsOutput, millionsCached input, %

Gemini 4 Argon: $40.00; per month
Qwen3.5 Plus: $8.80; per month

Standard listed rates, no batch or volume discounts.

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

Price against score, among all priced models

Overall score against output price per 1M tokens, one model per family. Pricing as of November 12, 2026.

Gemini 4 ArgonQwen3.5 Plus

2 models at the same price score higher than Gemini 4 Argon. The nearest is Gemini 4 Carbon (score 89.2, also $10.00 per 1M output tokens).
10 cheaper models score at least as high as Qwen3.5 Plus. The nearest is Mistral Large 4 (score 52.1, $2.10 per 1M output tokens).

Gray dots are the other priced models. The dark step line is the efficiency frontier: for a model under it, another model costs no more and scores at least as high.

See Qwen3.5 Plus on the full price vs performance chart

Specification differences

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

SpecificationGemini 4 ArgonQwen3.5 Plus

Context window

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

Gemini 4 Argon

Google Gemini 4 Argon model documentation

Qwen3.5 Plus

API model ID

Gemini 4 Argon

gemini-4-argon

Google Gemini 4 Argon model documentation

Qwen3.5 Plus

Not sourced

Cached-input rate

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

Gemini 4 Argon

$0.1 per 1M cached input tokens

Google Gemini API pricing

Qwen3.5 Plus

Not published

Documented inputs

Gemini 4 Argon

text, image, video, audio, pdf

Google Gemini 4 Argon model documentation

Qwen3.5 Plus

text, image, video

Qwen Cloud model page for qwen3.5-plus

Documented outputs

Gemini 4 Argon

text

Google Gemini 4 Argon model documentation

Qwen3.5 Plus

text

Qwen Cloud model page for qwen3.5-plus

Provider availability

Gemini 4 Argon

Generally Available · Gemini API, Google AI Studio

Google Gemini 4 Argon model documentation

Qwen3.5 Plus

Not sourced

Reasoning profile

Gemini 4 Argon

Reasoning

Qwen3.5 Plus

Reasoning

Weight access

Gemini 4 Argon

Proprietary

Qwen3.5 Plus

Proprietary

License

Gemini 4 Argon

Proprietary

Qwen3.5 Plus

Proprietary

Release date

Gemini 4 Argon

2026-09-30

Qwen3.5 Plus

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: Gemini 4 Argon has the higher public point estimate, 79.03 versus 49.06. Their conditional score ranges do not overlap. These ranges do not establish rank confidence.
Workload cost: Repository review: $0.13 vs $0.0272. Cache-heavy agent loop: $0.16 vs $0.112.
Context tradeoff: Both models list 1M.

Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Gemini 4 Argon or Qwen3.5 Plus?

Gemini 4 Argon has the higher public point estimate, 79.03 versus 49.06. Their conditional score ranges do not overlap. These ranges do not establish rank confidence. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Gemini 4 Argon or Qwen3.5 Plus?

Qwen3.5 Plus is not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, Gemini 4 Argon or Qwen3.5 Plus?

Qwen3.5 Plus is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, Gemini 4 Argon or Qwen3.5 Plus?

For the stated presets, chat costs $0.007 on Gemini 4 Argon and $0.0016 on Qwen3.5 Plus; repository review costs $0.13 and $0.0272; the cache-heavy agent loop costs $0.16 and $0.112. Qwen3.5 Plus has no published cached-input rate, so cached tokens use its listed input rate.

Which has the larger context window, Gemini 4 Argon or Qwen3.5 Plus?

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 evidence40 rows

Agentic

AutomationBench
Gemini 4 Argon51.3%
Source
Qwen3.5 Plus—
Not directly comparable
Finance Agent v2
Gemini 4 Argon65.4%
Source
Qwen3.5 Plus—
Not directly comparable
Terminal-Bench 4.0
Gemini 4 Argon57.40%
Source
Qwen3.5 Plus—
Not directly comparable
Agents' Last Exam
Gemini 4 Argon39.5%
Source
Qwen3.5 Plus—
Not directly comparable
OSWorld 2.0
Gemini 4 Argon69.2%
Source
Qwen3.5 Plus—
Not directly comparable
CWE-bench v1
Gemini 4 Argon68.0%
Source
Qwen3.5 Plus—
Not directly comparable
Terminal-Bench-Science 0.1 (6x verifier timeout)
Gemini 4 Argon57.6%
Source
Qwen3.5 Plus—
Not directly comparable
MazeBench
Gemini 4 Argon12%
Source
Qwen3.5 Plus—
Not directly comparable
OSWorld 2.1 Offline
Gemini 4 Argon74.7%
Source
Qwen3.5 Plus—
Not directly comparable
ExploitGym
Gemini 4 Argon39.5%
Source
Qwen3.5 Plus—
Not directly comparable
RoboDojo Sim
Gemini 4 Argon34.2%
Source
Qwen3.5 Plus—
Not directly comparable
CWE-bench
Gemini 4 Argon65.0%
Source
Qwen3.5 Plus—
Not directly comparable
Terminal-Bench 2.1 (Vals)
Gemini 4 Argon57.7%
Source
Qwen3.5 Plus—
Not directly comparable
JobBench
Gemini 4 Argon—
Qwen3.5 Plus18.5%
Source
Not directly comparable

Coding

ScarfBench
Gemini 4 Argon75.2%
Source
Qwen3.5 Plus—
Not directly comparable
DeepSWE
Gemini 4 Argon77.9%
Source
Qwen3.5 Plus—
Not directly comparable
FrontierSWE v2
Gemini 4 Argon55.0%
Source
Qwen3.5 Plus—
Not directly comparable
Vibe Code Bench
Gemini 4 Argon91.90%
Source
Qwen3.5 Plus15.74%
Source
Gemini 4 Argon leads this result
PostTrainBench v1.1
Gemini 4 Argon45.3%
Source
Qwen3.5 Plus—
Not directly comparable
Bug Hunt Bench
Gemini 4 Argon40.7 fixes
Source
Qwen3.5 Plus—
Not directly comparable
FrontierCode 2.0
Gemini 4 Argon26.3%
Source
Qwen3.5 Plus—
Not directly comparable
CursorBench 4.0
Gemini 4 Argon52.9%
Source
Qwen3.5 Plus—
Not directly comparable
PostTrainBench
Gemini 4 Argon40.4%
Source
Qwen3.5 Plus—
Not directly comparable

Reasoning

STEMBench
Gemini 4 Argon2.44
Source
Qwen3.5 Plus—
Not directly comparable
Graphwalks BFS 128K
Gemini 4 Argon99.7%
Source
Qwen3.5 Plus—
Not directly comparable
GraphWalks BFS 256K–1M
Gemini 4 Argon84.2%
Source
Qwen3.5 Plus—
Not directly comparable
ARC-AGI-1
Gemini 4 Argon98.50%
Source
Qwen3.5 Plus—
Not directly comparable
ARC-AGI-2
Gemini 4 Argon91.3%
Source
Qwen3.5 Plus—
Not directly comparable
ARC-AGI-3
Gemini 4 Argon46.3%
Source
Qwen3.5 Plus—
Not directly comparable
ARC-AGI-3 Provider Adapter
Gemini 4 Argon97.30%
Source
Qwen3.5 Plus—
Not directly comparable

Multimodal

ParseBench-2
Gemini 4 Argon84.20%
Source
Qwen3.5 Plus—
Not directly comparable
ExtractBench Pro
Gemini 4 Argon30%
Source
Qwen3.5 Plus—
Not directly comparable
Chartography (no tools)
Gemini 4 Argon71.6%
Source
Qwen3.5 Plus—
Not directly comparable
LVBench
Gemini 4 Argon91.7%
Source
Qwen3.5 Plus—
Not directly comparable
Blueprint-Bench 2
Gemini 4 Argon54.4%
Source
Qwen3.5 Plus—
Not directly comparable

Knowledge

LABBench2
Gemini 4 Argon88.8%
Source
Qwen3.5 Plus—
Not directly comparable
Morphology-to-molecule matching
Gemini 4 Argon25.2%
Source
Qwen3.5 Plus—
Not directly comparable

Instruction following

Gray Swan IPI (15 attempts)
Gemini 4 Argon0.7%
Source
Qwen3.5 Plus—
Not directly comparable

Math

FrontierMath v2 (Tiers 1-3)
Gemini 4 Argon85.965%
Source
Qwen3.5 Plus—
Not directly comparable
FrontierMath v2 (Tier 4)
Gemini 4 Argon78.049%
Source
Qwen3.5 Plus—
Not directly comparable

40 public results · 1 shared

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Last updated November 13, 2026

Gemini 4 Argon vs Qwen3.5 Plus

Decision reading

Which one for your work

Chat turn cost

Cache-heavy agent loop cost

Repository review cost

Coding work

Agentic work

Long documents

Which one for a specific job

Or describe your own job

What is actually comparable

Shape of the matched evidence

Category results, on a stated basis

Agentic

Coding

Reasoning

Multimodal

Knowledge

Multilingual

Instruction following

Math

What each workload costs

Chat turn

Repository review

Cache-heavy agent loop

Your workload

Price against score, among all priced models

Specification differences

Context window

API model ID

Cached-input rate

Documented inputs

Documented outputs

Provider availability

Reasoning profile

Weight access

License

Release date

If you already use one of these models

Questions

Which is better, Gemini 4 Argon or Qwen3.5 Plus?

Which is better for coding, Gemini 4 Argon or Qwen3.5 Plus?

Which is better for agentic tasks, Gemini 4 Argon or Qwen3.5 Plus?

Which costs less, Gemini 4 Argon or Qwen3.5 Plus?

Which has the larger context window, Gemini 4 Argon or Qwen3.5 Plus?

Benchmark evidence

Agentic

Coding

Reasoning

Multimodal

Knowledge

Instruction following

Math

Related comparisons

Watch Gemini 4 Argon vs Qwen3.5 Plus