Is local AI as good as ChatGPT? For most office tasks it is close enough. For the hardest ones it is not.
Short answer. For most office work, such as summaries, extraction, drafting and questions about your own documents, a good 27B-class open model is close enough to a hosted assistant that the gap rarely decides the outcome. On the hardest tests hosted flagships still lead: in Alibaba’s own table, Qwen3.8-27B scores 30.8 on Humanity’s Last Exam against 40.0 for the hosted model it lists, and 89.2 against 91.3 on GPQA Diamond. ChatGPT is also a product, with web search, voice, image tools and app connectors that a bare local model lacks. These are vendor-reported scores, so test any model on your own documents before relying on it.
01
What the benchmark tables show
Alibaba’s model card for Qwen3.8-27B, an Apache 2.0 open model released in August 2026, compares it with a hosted model, Opus 4.6 Max. Alibaba notes that the hosted model’s SWE-bench Pro score is its officially reported figure while the other scores were run on one harness, so that row is not like for like.
Test (Alibaba’s table, 2026)
Qwen3.8-27B (open, 27B)
Opus 4.6 Max (hosted)
GPQA Diamond (graduate-level science questions)
89.2
91.3
HLE (Humanity’s Last Exam, very hard multi-subject questions)
30.8
40.0
LiveCodeBench v6 (competitive coding)
90.3
88.8
SWE-bench Pro (fixing real software issues)
61.7
53.4
IFBench (following instructions)
79.5
62.5
02
Size still matters
OpenAI makes a similar point about its own open models: it says gpt-oss-120b reaches near-parity with its o4-mini on core reasoning benchmarks and runs on a single 80 GB GPU, while gpt-oss-20b is similar to o3-mini and runs in 16 GB of memory. Google DeepMind’s Gemma 4 card shows how much the size of the model matters.
Gemma 4 model
MMLU Pro
GPQA Diamond
E2B (2.3B effective parameters)
60.0%
43.4%
E4B (4.5B effective)
69.4%
58.6%
12B Unified
77.2%
78.8%
26B A4B (mixture of experts)
82.6%
82.3%
31B dense
85.2%
84.3%
03
What ChatGPT adds that a model does not
Web search and deep research.
Voice, and image creation.
Connectors to Microsoft 365, Google Drive, Slack, GitHub and other tools, listed on OpenAI’s Business plan.
Agent features that carry out multi-step work.
A vendor that updates the model for you.
04
Where a local model is enough, and where it is not
Usually enough: summarising meetings and documents, pulling out action items and fields, drafting letters and reports from your own material, and answering questions over your own files with the source shown.
Use a hosted model, or check harder: very hard multi-step reasoning, large code changes, questions that need current web information, and rare or niche knowledge.
Small models are weaker still. A 3B-class model failed ANVE’s own test for assigning meeting action items to the right person, which is why ANVE uses nothing smaller than 4B-class for minutes.
05
How to decide for your office
Take twenty real tasks from the last month, run them on both, and have someone who does the work score the answers without knowing which is which. If the content cannot leave the building, local is the only option and the quality gap is a trade you accept. Many offices will end up with both: a local default for client records and a hosted plan for general work, with each use labelled and logged.
ANVE One’s default is a 27B-class model (Qwen 3.8 27B) with a fast 4B model alongside it. Cloud models are optional, added by an administrator, and their answers are labelled. ANVE is pre-release.
06
Questions people ask
Can a local model be used commercially?
Qwen3.8-27B lists the Apache 2.0 licence on its Hugging Face card, and Gemma 4 lists Apache 2.0 as well. Both permit commercial use, subject to the licence conditions.
Does a bigger model always give better answers?
Usually on hard tasks: Google DeepMind’s card shows MMLU Pro rising from 69.4% for Gemma 4 E4B to 85.2% for the 31B. For simple extraction a smaller model can be enough, which is why a fast 4B model is often kept beside a larger one.
Can a local model use the internet like ChatGPT?
Only if the software around it adds a search tool and you allow it. By default a local model answers from its training and from the documents you give it.
How long will these comparisons stay true?
Not long. Both cards date from 2026 and new open models appear every few months, so treat any comparison as dated. This one is as of October 2026.
07
What is not real yet
No sealed ANVE unit exists; every image of the appliance on this site is a labelled render. The software runs today on a development machine. No customers yet, no certifications, no delivery date, and the final price is not announced.
Reservations are ₹999 in India or US$12 elsewhere, refundable in full until you confirm an order in writing (terms). Offices that cannot use cloud AI can apply to be one of ten design partners.
