Model Statistics
Time Period
Weekly Token Usage by Model
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Below is a list of AI models available on CodingFleet, along with statistics & benchmarks for the selected time period. The statistics are based on actual usage by CodingFleet users.
Legacy models are shown in the list but are grayed out and disabled. These models are no longer available.
The cost of the model is the number of credits required to use the model in a single request. For Unlimited and Elite users, the usage for 1-cost models is unlimited, while others are limited as shown in the pricing page.
| Model | Avg Speed (chars/s) The average speed of the model in characters per second, across all users utilizing this model. | N° Tokens The total number of tokens in both the prompt and the completion combined, across all users utilizing this model. | Cost The credit cost of utilizing this model in a request. Models with a cost of 2 or higher are considered premium models. | Vote Score The average vote score given to this model by CodingFleet users, where -1 is the lowest score and 1 is the highest. This is displayed only if there are 10 or more votes for the model. | LiveBench Coding The average LiveBench coding score (livebench.ai) | LiveBench Avg The average LiveBench average score (livebench.ai) | WebDev Arena WebDev Arena is an open-source benchmark evaluating AI capabilities in web development (https://web.lmarena.ai/leaderboard) |
|---|---|---|---|---|---|---|---|
Claude 3 Haiku
|
0.0 | 0 66 | 1 | - | - | - | - |
|
Claude 3 Opus
|
0.0 | 0 16 | 3 | - | - | - | - |
|
Claude 3 Sonnet
|
0.0 | 0 33 | 2 | - | - | - | - |
|
Claude 3.5 Haiku
|
203.9 | 417.3M 6 | 1 | -0.2 | 53.2 | 45.0 | 1133.8 |
|
Claude 3.5 Sonnet
|
203.7 | 3.8M 70 | 6 | - | 32.3 | 50.8 | 1239.3 |
|
Claude 3.7 Sonnet
|
220.9 | 301.2M 3 | 6 | 0.5 | 74.3 | 58.5 | 1356.7 |
|
Claude 3.7 Sonnet Thinking
|
166.3 | 211.8M 5 | 7 | - | 73.2 | 67.4 | 1356.7 |
|
Claude 4 Opus
|
140.3 | 13.6M 14 | 50 | - | 72.9 | 71.5 | 1405.5 |
|
Claude 4 Opus Thinking
|
125.9 | 35.2M 12 | 60 | - | 73.3 | 72.9 | 1405.5 |
|
Claude 4 Sonnet
|
193.2 | 575.7M 2 | 6 | 0.8 | 77.5 | 69.7 | 1381.8 |
|
Claude 4 Sonnet Thinking
|
149.0 | 1.2B 0 | 7 | 0.7 | 73.6 | 72.1 | 1381.8 |
|
Claude 4.1 Opus
|
131.4 | 15.9M 14 | 50 | - | - | - | - |
|
Claude 4.1 Opus Thinking
|
112.6 | 122.4M 6 | 60 | - | 74.0 | 73.5 | 1476.5 |
|
Claude Haiku 4.5
|
382.1 | 1.0B 0 | 1 | 0.6 | - | - | - |
|
Claude Haiku 4.5 Thinking
|
244.0 | 1.3B 0 | 1 | 1.0 | 72.8 | 71.4 | - |
|
Claude Opus 4.5
|
175.4 | 33.6M 12 | 15 | - | 77.5 | 76.0 | 1484.0 |
|
Claude Opus 4.5 Thinking
|
176.9 | 1.9B 0 | 17 | - | 79.7 | 79.8 | 1518.0 |
|
Claude Opus 4.6
|
150.8 | 12.3M 14 | 15 | - | 78.2 | 76.3 | 1504.0 |
|
Claude Opus 4.6 Thinking
|
134.5 | 1.7B 0 | 17 | - | 78.2 | 76.3 | 1503.0 |
|
Claude Sonnet 4.5
|
190.3 | 896.0M 0 | 7 | 0.2 | - | - | - |
|
Claude Sonnet 4.5 Thinking
|
151.4 | 3.7B 0 | 8 | 0.6 | 80.4 | 78.3 | 1397.0 |
|
Claude Sonnet 4.6
|
176.6 | 82.8M 9 | 7 | - | - | - | - |
|
Claude Sonnet 4.6 Thinking
|
156.1 | 836.7M 0 | 8 | 1.0 | 80.0 | 75.3 | - |
Codestral (2508)
|
828.0 | 16.1M 8 | 1 | - | - | - | - |
DeepSeek R1
|
273.3 | 1.4K 3 | 2 | - | - | - | - |
|
DeepSeek V3
|
204.1 | 1.1K 8 | 1 | - | - | - | - |
|
DeepSeek V3.2
|
86.7 | 622.1M 1 | 1 | 0.4 | 68.5 | 62.6 | - |
|
DeepSeek V3.2 Thinking
|
40.8 | 54.7M 8 | 1 | - | 64.6 | 66.6 | - |
GLM 4.6
|
159.0 | 13.0M 14 | 1 | - | - | - | - |
|
GLM 4.7
|
91.8 | 7.2M 14 | 1 | - | 73.1 | 58.1 | - |
|
GLM 5
|
124.2 | 11.5M 14 | 1 | - | 73.6 | 68.9 | 1456.0 |
GPT Image 1 Mini
|
0.0 | 0 1 | 1 | - | - | - | - |
|
GPT Image 1.5
|
0.0 | 0 8 | 1 | - | - | - | - |
|
GPT-3.5 Turbo
|
85.0 | 58 60 | 1 | - | - | - | - |
|
GPT-4
|
0.0 | 0 65 | 3 | - | - | - | - |
|
GPT-4 Turbo
|
43.7 | 62 37 | 10 | - | - | - | - |
|
GPT-4.1
|
231.7 | 549.2M 2 | 6 | 0.8 | 73.2 | 63.0 | 1256.5 |
|
GPT-4.1 mini
|
215.9 | 412.3M 3 | 1 | 0.1 | 72.1 | 59.1 | 1194.4 |
|
GPT-4o
|
297.3 | 64.5M 26 | 5 | - | 69.3 | 54.0 | 964.0 |
|
GPT-4o Mini
|
239.7 | 46.7M 33 | 1 | - | 43.2 | 41.3 | - |
|
GPT-5
|
201.1 | 186.5M 6 | 3 | 1.0 | 72.5 | 75.3 | - |
|
GPT-5 Mini
|
147.3 | 1.8B 0 | 1 | 0.5 | - | - | - |
|
GPT-5 Mini High
|
78.0 | 284.2M 4 | 2 | 1.0 | 66.4 | 72.2 | - |
|
GPT-5 Pro
|
35.0 | 12.9M 14 | 70 | - | 72.1 | 78.7 | - |
|
GPT-5 Thinking
|
90.9 | 517.5M 2 | 5 | - | 73.3 | 76.5 | - |
|
GPT-5 Thinking High
|
71.2 | 872.3M 0 | 5 | 1.0 | 75.3 | 78.6 | 1480.5 |
|
GPT-5.1
|
260.5 | 76.8M 9 | 3 | - | - | - | - |
|
GPT-5.1 Codex Max
|
222.8 | 22.9M 12 | 4 | - | 81.4 | 75.2 | - |
|
GPT-5.1 Codex Max High
|
183.8 | 72.6M 10 | 5 | - | 81.4 | 75.2 | - |
|
GPT-5.1 Codex Mini
|
223.6 | 344.0M 3 | 1 | - | 71.8 | 69.8 | 1248.0 |
|
GPT-5.1 Codex Mini High
|
218.5 | 50.5M 11 | 1 | - | 71.8 | 69.8 | 1248.0 |
|
GPT-5.1 Thinking
|
168.3 | 243.4M 4 | 5 | 1.0 | - | - | 1395.0 |
|
GPT-5.1 Thinking High
|
140.9 | 367.9M 3 | 5 | - | 72.5 | 72.5 | 1395.0 |
|
GPT-5.2
|
197.6 | 394.2M 3 | 4 | 0.3 | - | - | - |
|
GPT-5.2 Codex
|
178.4 | 83.5M 8 | 5 | - | 83.6 | 74.3 | - |
|
GPT-5.2 Codex
|
225.7 | 5.2M 15 | 8 | - | - | - | - |
|
GPT-5.2 Codex High
|
103.9 | 506.3M 3 | 7 | - | 83.6 | 74.3 | - |
|
GPT-5.2 Codex xHigh
|
95.6 | 55.9M 12 | 9 | - | 83.6 | 74.3 | - |
|
GPT-5.2 Thinking
|
144.9 | 292.9M 4 | 5 | - | - | - | - |
|
GPT-5.2 Thinking High
|
98.6 | 1.9B 0 | 6 | 0.5 | 76.1 | 73.6 | 1485.0 |
|
GPT-5.2 Thinking xHigh
|
60.8 | 269.1M 4 | 8 | - | - | - | - |
|
GPT-5.3 Codex
|
164.9 | 47.1M 11 | 5 | - | - | - | - |
|
GPT-5.3 Codex High
|
131.5 | 20.1M 14 | 7 | - | - | - | - |
|
GPT-5.3 Codex xHigh
|
79.3 | 113.4M 7 | 9 | - | - | - | - |
|
GPT-5.4
|
237.1 | 6.9M 14 | 6 | - | - | - | - |
|
GPT-5.4 Thinking
|
156.5 | 20.6M 13 | 8 | - | - | - | - |
|
GPT-5.4 Thinking High
|
185.8 | 8.9M 14 | 9 | - | - | - | - |
|
GPT-5.4 Thinking xHigh
|
134.2 | 29.7M 13 | 11 | - | - | - | - |
Gemini 1.5 Flash
|
0.0 | 0 65 | 1 | - | - | - | - |
|
Gemini 1.5 Pro
|
0.0 | 0 61 | 2 | - | - | - | - |
|
Gemini 2.0 Flash
|
572.1 | 154.1M 3 | 1 | 0.0 | - | - | - |
|
Gemini 2.0 Flash Thinking
|
430.1 | 2.9M 14 | 1 | - | 35.7 | 62.1 | 1030.1 |
|
Gemini 2.0 Pro (Exp)
|
320.6 | 20.0M 4 | 2 | - | 35.3 | 61.6 | 1088.6 |
|
Gemini 2.5 Flash
|
357.7 | 341.3M 3 | 1 | 0.3 | 60.3 | 69.9 | 1304.9 |
|
Gemini 2.5 Pro
|
180.7 | 357.2M 3 | 4 | 0.7 | 72.9 | 79.0 | 1409.1 |
|
Gemini 3 Flash
|
281.8 | 738.7M 1 | 1 | 0.5 | 73.9 | 73.6 | 1465.0 |
|
Gemini 3 Pro
|
162.3 | 411.1M 3 | 4 | 1.0 | 74.6 | 79.7 | 1481.0 |
|
Gemini 3.1 Pro
|
169.5 | 131.0M 6 | 4 | 1.0 | 76.5 | 79.9 | 1500.0 |
Grok-2
|
226.6 | 269.8K 14 | 2 | - | 26.1 | 48.1 | - |
|
Grok-3 (Beta)
|
256.6 | 4.4M 16 | 3 | - | 73.6 | 63.2 | - |
|
Grok-3 Mini (Beta)
|
276.5 | 8.0M 14 | 1 | - | 54.5 | 70.3 | - |
|
Grok-4
|
128.9 | 16.6M 14 | 5 | - | 71.3 | 72.1 | - |
|
Grok-4 Fast
|
370.7 | 72.8M 10 | 1 | - | - | - | - |
|
Grok-4.1 Fast
|
157.6 | 39.6M 14 | 1 | - | - | - | - |
Kimi K2 (0905)
|
184.7 | 1.6M 17 | 1 | - | 71.8 | 62.7 | - |
|
Kimi K2 Thinking
|
138.5 | 3.0M 17 | 1 | - | - | - | - |
|
Kimi K2.5
|
102.6 | 42.0M 12 | 1 | - | 77.9 | 69.1 | - |
Llama 3.1 405B
|
86.8 | 7.9M 15 | 2 | - | 42.7 | 52.4 | 813.7 |
|
Llama 3.1 70B
|
0.0 | 0 24 | 1 | - | 33.5 | 44.9 | - |
|
Llama 3.2 90B
|
161.2 | 195.1K 11 | 1 | - | - | - | - |
|
Llama 3.3 70B
|
554.7 | 14.5M 4 | 1 | - | 24.1 | 45.7 | - |
|
Llama 4 Maverick
|
315.6 | 29.6M 10 | 1 | - | 54.2 | 55.2 | 998.5 |
MiniMax M2.5
|
142.8 | 33.9M 12 | 1 | - | 70.7 | 60.1 | - |
|
Mistral Large 3
|
136.4 | 65.3M 9 | 1 | 1.0 | 62.9 | 50.3 | - |
|
Mistral Medium 3
|
261.5 | 6.9M 14 | 1 | - | 61.5 | 56.6 | 1160.1 |
|
Nano Banana 2.0
|
0.0 | 0 10 | 1 | - | - | - | - |
|
OpenAI o1
|
0.0 | 0 15 | 18 | - | - | - | 1045.2 |
|
OpenAI o1 Mini
|
0.0 | 0 55 | 2 | - | 48.1 | 57.8 | 1053.7 |
|
OpenAI o1 Preview
|
0.0 | 0 22 | 3 | - | - | - | - |
|
OpenAI o3
|
145.5 | 108.8M 8 | 4 | 1.0 | 77.9 | 72.0 | 1188.1 |
|
OpenAI o3-high
|
103.0 | 106.7M 8 | 5 | 1.0 | 76.7 | 74.6 | 1188.3 |
|
OpenAI o3-mini
|
255.3 | 36.1M 2 | 2 | - | 58.4 | 67.2 | 1091.7 |
|
OpenAI o3-mini-high
|
176.8 | 38.4M 6 | 2 | - | 65.5 | 71.4 | 1136.2 |
|
OpenAI o4-mini
|
185.2 | 137.8M 6 | 2 | -0.1 | - | - | 1095.1 |
|
OpenAI o4-mini-high
|
123.0 | 67.0M 11 | 2 | 0.5 | - | - | - |
Qwen 3.5 Flash
|
318.6 | 164.5K 14 | 1 | - | - | - | - |
|
Qwen 3.5 Plus
|
187.6 | 30.5M 13 | 1 | - | - | - | - |
|
Qwen2.5-Coder 32B
|
292.6 | 865.2K 9 | 1 | - | 56.9 | 46.2 | 904.1 |
|
Qwen3 235B A22B
|
159.6 | 23.6M 12 | 1 | - | 66.4 | 64.9 | - |
|
Qwen3 Coder
|
291.2 | 3.3M 15 | 2 | - | 73.2 | 60.5 | - |