whatmodel.sh / GPT-3.5 Turbo (1106)
GPT-3.5 Turbo (1106)
↗ share
+ contribute
GPT-3.5 Turbo (1106) is a closed-weights language model from OpenAI, released November 2023. Licence: proprietary.
Catalogue identity notes
Comparison model from the Epoch AI internal-evaluation CSVs (Epoch release date 2023-11-06). Dated API snapshot gpt-3.5-turbo-1106. OpenAI deprecations page: shutdown date 2026-09-28, so treated as retired.
$ how it compares
The LLMs ranked either side of GPT-3.5 Turbo (1106), out of 828 with a score, then more from OpenAI.
| # | model | score | where | ||
|---|---|---|---|---|---|
| 493 |  OLMo 2 13B Instruct (1124) | 46±1 | local | ||
| 494 |  Falcon-H1 7B Instruct | 46±3 | local | ||
| 495 | GPT-3.5 Turbo (1106) | 46±1 | comparison only | ||
| 496 |  Cogito v1 Preview Llama 3B | 46±4 | local | ||
| 497 |  Code Llama 70B Instruct | 46±1 | local | ||
| more from OpenAI | |||||
| 1 | GPT-6 Astra | 87±1 | api $20.00/M | ||
| 3 | GPT-6.1 Sol | 85±1 | api $4.00/M | ||
| 7 | GPT-6 Sol | 83±1 | api $4.00/M | ||
$ what it's good at
coding▁▁▁▃▅▇█▇▅▄▃▁ #323 of 524 · 50% of its score · 3 tests
Beats Qwen3-VL 32B Instruct, Solar Open 100B (102B-A12B), GLM-4.7-Flash here, though they rank higher overall. Trails DeepSeek LLM 67B Chat, Mistral NeMo Instruct (2407), QwQ-32B-Preview here, though they rank lower overall.
chat & writing▁▁▁▃▅▄▆█▇▇▇▃ #367 of 463 · 30% of its score · 6 tests
Beats Gemma 4 E4B, OpenThinker3 7B, Gemma 4 E2B here, though they rank higher overall. Trails LFM2 350M, Gemma 3 1B, Flan-T5 XXL here, though they rank lower overall.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| AlpacaEval 2 length-controlled | 19.3% ✎ | ▁▂▂▃▆▆█▆▄▄▁▁ beats 51/122 | 12% |
| Arena-Hard (v0.1, GPT-4-1106 judge) | 18.9% ✎ | ▂▁▁▅█▅▄▃▃▅▃▁ beats 13/60 | 8.2% |
| Polyrating rating (bias-aware re-fit of Chatbot Arena votes, mid-2024) | 1106.0 ✎ | ▂▁▂▁▃▇█▆▇▄▂▂ beats 50/95 | 3.2% |
| LMArena (text) | 1204.2 ✎ | ▁▁▁▂▃▃▃▆▆▇█▃ beats 71/379 | 3.2% |
| MT-Bench (GPT-4 single-answer grading, LMSYS runs) | 8.3200 MT-Bench score (1-10) ✎ | ▆▂▂▆▆▄██▂▄▄▆ beats 24/28 | 2.8% |
| AlpacaEval 1.0 win rate (vs text-davinci-003, GPT-4 judge) | 86.3% ✎ | ▂▂·▆·▇▃▆█▆▄▂ beats 24/45 | 0.5% |
math▁▂▃▅▇▅▅█▄▁▁▁ #383 of 462 * · 4.8% of its score · 1 test
Beats GPT-3.5 Turbo (0125) here, though they rank higher overall. Trails Qwen3 0.6B, Gemma 7B (base), DeepSeek R1 Distill Qwen 1.5B here, though they rank lower overall.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| MATH level 5 | 15.9% ✎ | ▂▂▅▆▄█▆▃▅▂▃▄ beats 14/92 | 4.8% |
other tests2 not in a task · 15% of its score
| test | result | vs the others in its run | counts |
|---|---|---|---|
| LiveBench 2024-07-26 | 34.1% ✎ | ▁▁▁▂▂▃▂█▆▃▅▃ beats 34/61 | 13% |
| GPQA Diamond | 28.0% ✎ | ▁▁▁▃▂▄▆▄▅▇█▅ beats 13/208 | 2.6% |
$ where to run it
No verified API or download recorded yet · add one
$ how the score was worked out · EvalPlus / EvalPerf published… 50%, LiveBench model judgments (HF… 13%, AlpacaEval 1.0 and 2.0 leader… 12% and 5 more
Each result implies a score on its own, after adjusting for how hard its test is and who ran it. The score is their weighted average, with a small pull toward the middle for thinly tested models. Each test's weight is its counts column above; here it's added up by who ran the tests. How it works
$ improve this page
Use a short GitHub form or edit the data through a pull request. Every number needs a source; here's which ones we can use.
data updated · sources and licences · json