Part of Best LLM for AI Agents
Best LLM for Computer & Browser Use
Claude Opus 5.5 is the provisional first pick for Computer & Browser Use as of October 20, 2026, while independent task measurements are still limited.[1][2][3][4] It ranks #1 of 48 on LMArena's agentic arena (score 20.4), measuring tool-use and multi-step task performance from human preference. GPT-6 Astra is the next-ranked alternative. Ranks second on LMArena's agentic arena and demonstrates strong visual reasoning when inspecting flow configurations as images, though first-hand reports document silent failures and premature safety caps during web-based computer use.
About this recommendation
- Updated
- Evidence through
- Sources
- 11
- Revision
- v107
Decision audit
Why this result
Inspect the inputs and the computed order behind the recommendation.
Models screened
24
live candidates
Evaluation feeds
3
task-weighted
Winner coverage
17%
intended feed weight
Largest provider share
3 of 8
Anthropic
Anthropic: Claude Opus 5.5 leads the measured task comparison with limited independent task measurements. Community volume, release age and usage popularity add no ranking points.
Real-world track record is still developing. The recommendation can lead on independent measurements while practitioner reports accumulate.
Sources evaluated
These are the weights used in scoring. Missing measurements are omitted from each model’s average. A feed with no result for any model released in the last 60 days is stale and does not score until it catches up.
| Evaluation feed | Weight | Winner result | Field measured |
|---|---|---|---|
| OSWorld Verifiedstale | 0% | no current result | 0/24 |
| LMArena AgentObserved 2026-10-19 · evaluation date not supplied · max effort | 100% | #1 | 24/24 |
| Berkeley Function Callingstale | 0% | no current result | 0/24 |
Provider concentration
Each exact model is scored separately; provider identity is not a ranking input.
- Anthropic3 models
- Google2 models
- OpenAI2 models
- Meta1 model
Decision table
Every published model is shown in computed order. Practitioner sources are distinct community threads, not the citations repeated in the prose below.
Anthropic · coverage 17% · provisional evidence
#1 LMArena Agent
OpenAI · coverage 17% · provisional evidence
#2 LMArena Agent
Anthropic · coverage 17% · provisional evidence
#3 LMArena Agent
OpenAI · coverage 17% · provisional evidence
#4 LMArena Agent
Anthropic · coverage 17% · provisional evidence
#5 LMArena Agent
Google · coverage 17% · provisional evidence
#6 LMArena Agent
Meta · coverage 17% · provisional evidence
#12 LMArena Agent
Google · coverage 17% · provisional evidence
#13 LMArena Agent
Task score averages the available, task-weighted measurements. Benchmark positions compare models matched to our catalog. Models measured by at least two independent evaluator families are considered first. Missing tests, practitioner report counts, popularity and release age add no points. Coverage describes evidence breadth, not a probability of correctness. Scores within two points are shown as close under this policy; this is not a statistical confidence interval. When the leading scores are that close, the model measured by more evaluator families ranks first.
- 01
Claude Opus 5.5Anthropic · $4 in / $20 out per M tokens · 1M context
Claude Opus 5.5 ranks #1 of 48 on LMArena's agentic arena (score 20.4), measuring tool-use and multi-step task performance from human preference.
Best when: Its strongest result for this task is on LMArena Agent, which measures tool calling and multi-step control across a long task.No practitioner reports are linked yet, so no cautions are listed. Absence of reports is not evidence of reliability.
- 02
GPT-6 AstraOpenAI · $10 in / $50 out per M tokens · 1.1M context
Ranks second on LMArena's agentic arena and demonstrates strong visual reasoning when inspecting flow configurations as images, though first-hand reports document silent failures and premature safety caps during web-based computer use.
Best when: Deploy when the task benefits from visual inspection of interface screenshots, as it shows remarkable intelligence interpreting flow configurations and pipeline images.Watch out for
- Expect potential stalls in production phases where planning completes but no file or tool completions emit, triggering inactivity watchdogs.
- Anticipate safety cap triggers from consecutive invalid steps when web fetches fail with HTTP 403 or timeouts, even at low token consumption percentages.
- 03
Claude Fable 5.1Anthropic · $10 in / $50 out per M tokens · 1M context
Claude Fable 5.1 ranks #3 of 48 on LMArena's agentic arena (score 14.3), measuring tool-use and multi-step task performance from human preference.
Best when: Its strongest result for this task is on LMArena Agent, which measures tool calling and multi-step control across a long task.No practitioner reports are linked yet, so no cautions are listed. Absence of reports is not evidence of reliability.
- 04
GPT-6.1 SolOpenAI · $2 in / $10 out per M tokens · 1.1M context
GPT-6.1 Sol ranks #4 of 48 on LMArena's agentic arena (score 13.7), measuring tool-use and multi-step task performance from human preference.
Best when: Its strongest result for this task is on LMArena Agent, which measures tool calling and multi-step control across a long task.No practitioner reports are linked yet, so no cautions are listed. Absence of reports is not evidence of reliability.
- 05
Claude Sonnet 5.5Anthropic · $2 in / $10 out per M tokens · 1M context
Claude Sonnet 5.5 ranks #5 of 48 on LMArena's agentic arena (score 12.8), measuring tool-use and multi-step task performance from human preference.
Best when: Its strongest result for this task is on LMArena Agent, which measures tool calling and multi-step control across a long task.No practitioner reports are linked yet, so no cautions are listed. Absence of reports is not evidence of reliability.
- 06
Gemini 4 ArgonGoogle · $2 in / $10 out per M tokens · 1.0M context
Gemini 4 Argon ranks #6 of 48 on LMArena's agentic arena (score 12.1), measuring tool-use and multi-step task performance from human preference.
Best when: Its strongest result for this task is on LMArena Agent, which measures tool calling and multi-step control across a long task.No practitioner reports are linked yet, so no cautions are listed. Absence of reports is not evidence of reliability.
- 07
Muse WonderMeta · $4 in / $20 out per M tokens · 1.0M context
Muse Wonder ranks #12 of 48 on LMArena's agentic arena (score 3.8), measuring tool-use and multi-step task performance from human preference.
Best when: Its strongest result for this task is on LMArena Agent, which measures tool calling and multi-step control across a long task.No practitioner reports are linked yet, so no cautions are listed. Absence of reports is not evidence of reliability.
- 08
Gemini 3.8 FlashGoogle · $0.83 in / $4.13 out per M tokens · 1.0M context
Gemini 3.8 Flash ranks #13 of 48 on LMArena's agentic arena (score 3.7), measuring tool-use and multi-step task performance from human preference.
Best when: Its strongest result for this task is on LMArena Agent, which measures tool calling and multi-step control across a long task.No practitioner reports are linked yet, so no cautions are listed. Absence of reports is not evidence of reliability.
Frequently asked
- What is the best model for Computer & Browser Use?
- Claude Opus 5.5 ranks first as of October 20, 2026. Claude Opus 5.5 ranks #1 of 48 on LMArena's agentic arena (score 20.4), measuring tool-use and multi-step task performance from human preference.[1]
- What is the best alternative to Claude Opus 5.5?
- GPT-6 Astra ranks second. Ranks second on LMArena's agentic arena and demonstrates strong visual reasoning when inspecting flow configurations as images, though first-hand reports document silent failures and premature safety caps during web-based computer use.[2][3][4]
Sources
- 1
“Within the 48 catalog models matched to this evaluation: Ranks #1 of 48 on LMArena's agentic arena (score 20.4), measuring tool-use and multi-step task performance from human preference.”
LMArena agentic arena · Benchmark · Oct 19, 2026 - 2
“Within the 48 catalog models matched to this evaluation: Ranks #2 of 48 on LMArena's agentic arena (score 15.1), measuring tool-use and multi-step task performance from human preference.”
LMArena agentic arena · Benchmark · Oct 19, 2026 - 3
“Feature Request I propose adding a capability that captures the current flow/pipeline configuration as an image and feeds it as a multimodal input to the Langflow Assistant Motivation Recently, I tested advanced multimodal agents (such as GPT-6 Astra using a Flow Edit MCP and Computer Use, as well as SOL-level models). I observed that these agents demonstrate remarkable intelligence when they can visually inspect the entire flow configuration and pipeline as an "image." By converting th…”
YamonBot · GitHub · Sep 7, 2026 - 4
epic: 网页取证鲁棒性路线图（403 / WAF / 失败级联 / 浏览器后端）
Original-language excerpt:“跟踪「网页取证鲁棒性」这一整条线的 issue。起因是 GPT-6 Astra 探索性调研连续两次失败，根因不在研究逻辑，而在读不到网页以及读不到之后的处理方式。 根因回顾 失败 run work_dir/exploratory/2026-09-06_070616： - 19 次 content-fetch 全部失败：17 次 HTTP 403（openai.com ×9、reddit.com ×3、futurumgroup.com ×3、medium.com ×2）+ 2 次 15s 超时（deploymentsafety.openai.com 的 PDF，每次墙钟 45.7s） - 这些传输失败被计入 consecutiveInvalidSteps，在 explorationTokens = 98296 / 下限 600000（16%）时触发 safety_cap - 报告阶段以 REPORT_OUTPUT_INVALID 失败，错误信息却是「minimum 200 characters; rece…”
imjszhang · GitHub · Sep 6, 2026 - 5
“Problem A GPT-6-Astra prototype that needs one large index.html can finish planning, enter production, then emit no file/tool completion while Codex repeatedly reconnects. OpenDesign eventually terminates it through the inactivity watchdog. An unrelated MCP OAuth warning can then make the run appear to require a Codex login. Environment - OpenDesign tag open-design-v0.22.2 - Source commit 73953213a6fec2c8092e8e77d229a3074aa828a9 - Package/runtime version 0.22.1 - Codex CLI was `0.…”
jerryfane · GitHub · Sep 13, 2026 - 6
“Within the 48 catalog models matched to this evaluation: Ranks #3 of 48 on LMArena's agentic arena (score 14.3), measuring tool-use and multi-step task performance from human preference.”
LMArena agentic arena · Benchmark · Oct 19, 2026 - 7
“Within the 48 catalog models matched to this evaluation: Ranks #4 of 48 on LMArena's agentic arena (score 13.7), measuring tool-use and multi-step task performance from human preference.”
LMArena agentic arena · Benchmark · Oct 19, 2026 - 8
“Within the 48 catalog models matched to this evaluation: Ranks #5 of 48 on LMArena's agentic arena (score 12.8), measuring tool-use and multi-step task performance from human preference.”
LMArena agentic arena · Benchmark · Oct 19, 2026 - 9
“Within the 48 catalog models matched to this evaluation: Ranks #6 of 48 on LMArena's agentic arena (score 12.1), measuring tool-use and multi-step task performance from human preference.”
LMArena agentic arena · Benchmark · Oct 19, 2026 - 10
“Within the 48 catalog models matched to this evaluation: Ranks #12 of 48 on LMArena's agentic arena (score 3.8), measuring tool-use and multi-step task performance from human preference.”
LMArena agentic arena · Benchmark · Oct 19, 2026 - 11
“Within the 48 catalog models matched to this evaluation: Ranks #13 of 48 on LMArena's agentic arena (score 3.7), measuring tool-use and multi-step task performance from human preference.”
LMArena agentic arena · Benchmark · Oct 19, 2026
Rankings synthesized from community evidence and open benchmarks. See methodology. Not driven by vendor marketing.