LLMs — Technology data 2026 | Stack Overflow Developer Survey

Developer Survey 2026

Question

Which LLM model vendors for AI tools have you used for work in the past year? Which would you like to use next year? Select all that apply.

scale
Optional
v2026.1

Data

	Respondents	Percent
Anthropic	8,871	74.6%
OpenAI	8,834	74.3%
Google AI	6,483	54.5%
Microsoft	3,142	26.4%
DeepSeek	2,253	18.9%
Alibaba Qwen	1,203	10.1%
Mistral AI	1,162	9.8%
xAI	906	7.6%
Meta AI	754	6.3%
Moonshot AI	479	4.0%
Other	427	3.6%
Zhipu AI	263	2.2%
Snowflake	234	2.0%
Databricks (DBRX)	194	1.6%
Black Forest Labs	120	1.0%
Cohere	112	0.9%
Stability AI	102	0.9%
Voyage AI (MongoDB)	92	0.8%
Cascade	82	0.7%
01.AI	56	0.5%
Luel	41	0.3%
Guide Labs	39	0.3%
Reka	39	0.3%
Minimax	13	0.1%
GLM	4	0.0%

Use this data

Citation

Response data is released under the ODbL 1.0, which asks that you attribute it.

Stack Exchange Inc. (2026). “LLMs”. Stack Overflow Developer Survey 2026. Licensed under ODbL 1.0. https://survey.stackoverflow.co/2026/technology/data/llm

JSON

Structured for code, with the question, the year and the source url alongside the numbers.

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  "question": "LLMs",
  "dataId": "LLM",
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    {
      "response": "Anthropic",
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      "pct": 0.746
    },
    {
      "response": "OpenAI",
      "count": 8834,
      "pct": 0.743
    },
    {
      "response": "Google AI",
      "count": 6483,
      "pct": 0.545
    },
    {
      "response": "Microsoft",
      "count": 3142,
      "pct": 0.264
    },
    {
      "response": "DeepSeek",
      "count": 2253,
      "pct": 0.189
    },
    {
      "response": "Alibaba Qwen",
      "count": 1203,
      "pct": 0.101
    },
    {
      "response": "Mistral AI",
      "count": 1162,
      "pct": 0.098
    },
    {
      "response": "xAI",
      "count": 906,
      "pct": 0.076
    },
    {
      "response": "Meta AI",
      "count": 754,
      "pct": 0.063
    },
    {
      "response": "Moonshot AI",
      "count": 479,
      "pct": 0.04
    },
    {
      "response": "Other",
      "count": 427,
      "pct": 0.036
    },
    {
      "response": "Zhipu AI",
      "count": 263,
      "pct": 0.022
    },
    {
      "response": "Snowflake",
      "count": 234,
      "pct": 0.02
    },
    {
      "response": "Databricks (DBRX)",
      "count": 194,
      "pct": 0.016
    },
    {
      "response": "Black Forest Labs",
      "count": 120,
      "pct": 0.01
    },
    {
      "response": "Cohere",
      "count": 112,
      "pct": 0.009
    },
    {
      "response": "Stability AI",
      "count": 102,
      "pct": 0.009
    },
    {
      "response": "Voyage AI (MongoDB)",
      "count": 92,
      "pct": 0.008
    },
    {
      "response": "Cascade",
      "count": 82,
      "pct": 0.007
    },
    {
      "response": "01.AI",
      "count": 56,
      "pct": 0.005
    },
    {
      "response": "Luel",
      "count": 41,
      "pct": 0.003
    },
    {
      "response": "Guide Labs",
      "count": 39,
      "pct": 0.003
    },
    {
      "response": "Reka",
      "count": 39,
      "pct": 0.003
    },
    {
      "response": "Minimax",
      "count": 13,
      "pct": 0.001
    },
    {
      "response": "GLM",
      "count": 4,
      "pct": 0
    }
  ]
}

Markdown

A formatted table, ready to paste into a document, an issue or a prompt.

|  | Respondents | Percent |
| --- | ---: | ---: |
| Anthropic | 8,871 | 74.6% |
| OpenAI | 8,834 | 74.3% |
| Google AI | 6,483 | 54.5% |
| Microsoft | 3,142 | 26.4% |
| DeepSeek | 2,253 | 18.9% |
| Alibaba Qwen | 1,203 | 10.1% |
| Mistral AI | 1,162 | 9.8% |
| xAI | 906 | 7.6% |
| Meta AI | 754 | 6.3% |
| Moonshot AI | 479 | 4.0% |
| Other | 427 | 3.6% |
| Zhipu AI | 263 | 2.2% |
| Snowflake | 234 | 2.0% |
| Databricks (DBRX) | 194 | 1.6% |
| Black Forest Labs | 120 | 1.0% |
| Cohere | 112 | 0.9% |
| Stability AI | 102 | 0.9% |
| Voyage AI (MongoDB) | 92 | 0.8% |
| Cascade | 82 | 0.7% |
| 01.AI | 56 | 0.5% |
| Luel | 41 | 0.3% |
| Guide Labs | 39 | 0.3% |
| Reka | 39 | 0.3% |
| Minimax | 13 | 0.1% |
| GLM | 4 | 0.0% |

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