Opus leads the composite. Argon costs less today.
In the independent snapshot below, Opus 5.5 leads overall and on terminal coding, while Argon leads the automation test and has a lower task bill. Google’s launch discount ends November 30: price your actual workload at both schedules before committing.
Difficult coding work
Use the stronger composite result as a starting hypothesis, then check your repository’s tests and review quality.
Cost-sensitive automation
Test the automation advantage against your tools, failure rate and total billable output.
This is an editorial comparison of Gemini 4 Argon and Claude Opus 5.5. VSModels has not run a paid head-to-head benchmark and does not currently offer calls to this pair. Published tests and our suggested checks are identified separately.
Five numbers. Read the configuration first.
| Metric | Argon · High | Opus 5.5 · Max, Default Fallback |
|---|---|---|
| Intelligence Index v4.3.2 ↑ | 53 | 58 |
| AutomationBench-AA ↑ | 78% | 70% |
| Terminal-Bench 4.0 ↑ | 57% | 60% |
| Weighted cost / Index task ↓ | $1.99 | $5.98 |
| Weighted output tokens / task | 62k | 119k |
↑ Higher is better; ↓ lower is better. Effort labels are different settings, not matched compute budgets. Task cost and token use are weighted benchmark results, not a quote for your app. Argon latency fields were blank in the comparison snapshot; no speed ranking is inferred.
The Index combines multiple evaluations. Its methodology weights each evaluation’s costs, including the relevant token categories. A lower token rate can coexist with a higher total task bill when a model thinks longer or makes more calls. Choose benchmarks that resemble the job you need done.
The same model changed when the agent changed.
OhMyUnicorn published a Three.js planet-building experiment using the same brief and project notes. The updated page adds a second Argon run in a different agent. Its author-reported results are more useful than a single “faster” headline:
| Model and agent | Build time | Cost | Inspected its page? |
|---|---|---|---|
| Argon · Gemini CLI | 5.5 min | $1.58 | Browser attempt failed |
| Argon · Antigravity CLI | 12.4 min | $1.45 | 7 screenshots |
| Opus 5.5 · Claude Code | 14.0 min | $2.54 | 3 inspections |
The author describes a cleaner Argon result with Antigravity, and greater close-up detail in the Opus result. This is one task, without a blind judge or repeated runs for each agent. Different tools, settings, dates and screenshot work limit model-only conclusions. The Argon page even warns that a benchmark drawer inside its generated demo contains invented figures: use the author’s external table.
Some waiting time belonged to the browser.
The original report attributes roughly half the build time to software-rendered screenshots. It lists visible defects, including a plane-view obstruction and cars passing through one another. The $2.54 includes substantial cache activity, not just the generated page’s text.
OhMyUnicorn · original Opus build and limitations, September 22Readers disagree about what the demo proves.
The discussion includes praise for the visual differences and criticism of mobile usability and one-shot coding tests. These are individual reactions, not additional controlled runs. The publisher’s updated experiment is the source for the numbers above.
Reddit · author discussion and critical responsesSimilar context headlines. Different output paths.
| Specification | Gemini 4 Argon | Claude Opus 5.5 |
|---|---|---|
| API model ID | gemini-4-argon | claude-opus-5-5 |
| Context | 1,048,576 tokens shared by input, thinking and output | 1M tokens |
| Standard output | 65,536 tokens by default, synchronous | 128K tokens |
| Extended output path | Background long decode; up to remaining unified context | 300K via Message Batches API beta |
| Documented inputs | Text, images, video, audio and PDF | Text and images; PDF support documented |
| Output modality | Text | Text |
| Reasoning controls | Low / medium / high; medium default | Adaptive thinking always on; medium default |
| Cache behavior | Implicit caching; no explicit cache objects | Cache writes and reads billed separately |
“Up to 1M output” is not a default Argon reply length: input and thinking consume the same window. Neither model is an image generator. For tool-heavy software, check API behavior as well as benchmarks: Opus 5.5 no longer accepts disabled thinking or forced-tool settings, and its fallback behavior matters to how an evaluation is labeled.
Argon’s two price schedules change the comparison.
| Component | Argon through Nov 30 | Argon from Dec 1 | Opus 5.5 |
|---|---|---|---|
| Uncached input | $2 | $4 | $4 |
| Output, including thinking | $10 | $20 | $20 |
| Cached input / read | $0.10 · implicit hit | $0.20 · implicit hit | $0.20 · cache read |
Argon’s introductory uncached rates are half Opus’s listed rates. From December 1, Google’s published schedule matches those headline rates. That does not make task bills equal: usage, caching and agent calls still differ. Opus cache writes cost $5/1M for five minutes or $8/1M for one hour. Consumer subscriptions are separate from these API rates.
Change the usage. Then change the date.
The default example uses equal token counts as a transparent assumption. For a real estimate, enter each model’s measured billable usage, including thinking; a matching prompt need not produce matching token counts.
Illustrative Standard, uncached text API estimate using the schedule checked Oct 15, 2026. Set each model’s own token usage; tokenization and thinking can differ. Excludes cache writes/reads, tools, search, batch/flex/fast modes, regional premiums, taxes and gateway margins. Argon uses the default synchronous output limit here; long decode is outside this estimate. No provider call or VSModels credit quote is made.
Keep a small acceptance test.
Repository work
Use an existing bug and hidden regression tests. Score correctness, review findings, unwanted edits and the work needed to finish.
Automation
Replay a representative workflow in a safe test environment. Count successful outcomes, tool failures and recovery steps.
Long documents
Plant checkable facts across the document. Verify citations and omissions rather than assuming a large context means perfect recall.
Cost and latency
Track end-to-end time, retries, cache activity and billable thinking. Repeat the same job and keep failed attempts in the total.
These are suggested checks, not VSModels results. Fix the model version, agent, tool permissions and effort before comparing; record every exception.
What “Argon vs Opus” leaves out.
Which models does this comparison cover?
Google Gemini 4 Argon and Anthropic Claude Opus 5.5. “Opus” is a model family name; results for older Opus releases do not answer this comparison.
Is Argon faster than Opus 5.5?
The coding example finished sooner on Argon, but time changed considerably between two agents using the same model. A single task and missing comparable API latency data do not establish a universal speed ranking.
Does equal pricing from December mean equal cost?
No. It means the published uncached input/output rates match. Different thinking, tool calls, cache behavior and retries can produce different bills.
Can I test this pair on VSModels?
Not currently. This guide is independent editorial coverage. The separate text-comparison interface has its own executable model list and activation controls; this article adds neither model to it.
A benchmark, an experiment, and their boundaries.
Compiled by VSModels from official documents, an independent evaluator and primary author reports. Checked October 15, 2026. We have not independently replicated the model runs. Dynamic benchmark values, prices and access can change; our quoted numbers are dated snapshots. The original links let you inspect the full methods and playable results.
- Google · Gemini 4 Argon model specifications
- Google · Argon changes, reasoning and long decode
- Google · Gemini API pricing
- Anthropic · Claude Opus 5.5 specifications
- Anthropic · thinking, tools and fallback changes
- Artificial Analysis · Argon High vs Opus Max, Default Fallback
- Artificial Analysis · Intelligence Index methodology
- OhMyUnicorn · same-brief Argon / Opus experiment, updated October 14
- OhMyUnicorn · original Opus build and limitations, September 22
- Reddit · author discussion and critical responses