How Many AI Tokens Can I Get for My Budget?

Enter a monthly dollar amount and instantly see how many tokens each AI model gives you. Last updated:

How far does my AI budget go? Different models have wildly different per-token rates. A $50 monthly budget buys you about 1,333 million input tokens on Command R7B but only about 2 million on GPT-5.4 Pro. This calculator divides your budget by each model's input and output rates and ranks every model by total token allowance, so you can find the best bang for your buck.

Your Budget

$25.00 input / $25.00 output

Token Allowance per Model — $50.00/mo Budget

Sorted by total tokens (most to least). Split: 50% input / 50% output.

#ModelProviderInput TokensOutput TokensTotal Tokens
1Embed v3 Englishcohere250.0MInfinityBInfinityB
2Embed v3 Multilingualcohere250.0MInfinityBInfinityB
3Rerank v3cohere12.5MInfinityBInfinityB
4Command R7Bcohere666.7M166.7M833.3M
5Llama 3.1 8b Instantgroq500.0M312.5M812.5M
6GPT-OSS 20B (Together)together500.0M125.0M625.0M
7GPT-5 nanoopenai500.0M62.5M562.5M
8Ministral 3Bmistral250.0M250.0M500.0M
9Gemini 2.0 Flash-Litegoogle333.3M83.3M416.7M
10GPT OSS Safeguard 20Bgroq333.3M83.3M416.7M
11Openai/gpt Oss 20bgroq333.3M83.3M416.7M
12Llama 4 Scoutmeta312.5M83.3M395.8M
13Devstral Small 2mistral250.0M83.3M333.3M
14Ministral 8Bmistral166.7M166.7M333.3M
15Mistral NeMomistral166.7M166.7M333.3M
16Mistral Small 4mistral250.0M83.3M333.3M
17Pixtral 12Bmistral166.7M166.7M333.3M
18Gemini 2.0 Flashgoogle250.0M62.5M312.5M
19Gemini 2.5 Flash-Litegoogle250.0M62.5M312.5M
20GPT-4.1 nanoopenai250.0M62.5M312.5M
21Llama 4 Scout 17B 16E Instructgroq227.3M73.5M300.8M
22DeepSeek V4 Flashdeepseek178.6M89.3M267.9M
23Ministral 14Bmistral125.0M125.0M250.0M
24Command R 08-2024cohere166.7M41.7M208.3M
25GPT-4o miniopenai166.7M41.7M208.3M
26GPT-OSS 120B (Together)together166.7M41.7M208.3M
27Llama 4 Maverickmeta166.7M41.7M208.3M
28Openai/gpt Oss 120bgroq166.7M41.7M208.3M
29Mistral 7Bmistral100.0M100.0M200.0M
30Grok 4 1 Fast Non Reasoningxai125.0M50.0M175.0M
31Grok 4 1 Fast Reasoningxai125.0M50.0M175.0M
32Grok 4.1 Fastxai125.0M50.0M175.0M
33GPT-5.4 nanoopenai125.0M20.0M145.0M
34Qwen3 32Bgroq86.2M42.4M128.6M
35Gemini 3.1 Flash-Litegoogle100.0M16.7M116.7M
36GPT-5 miniopenai100.0M12.5M112.5M
37Codestralmistral83.3M27.8M111.1M
38MiniMax M2.7 (Together)together83.3M20.8M104.2M
39Gemini 2.5 Flashgoogle83.3M10.0M93.3M
40GPT-4.1 miniopenai62.5M15.6M78.1M
41Devstral Medium 2mistral62.5M12.5M75.0M
42Mistral Medium 3mistral62.5M12.5M75.0M
43Llama 3.3 70b Versatilegroq42.4M31.6M74.0M
44Mixtral 8x7Bmistral35.7M35.7M71.4M
45Magistral Smallmistral50.0M16.7M66.7M
46Mistral Large 3mistral50.0M16.7M66.7M
47Gemini 3 Flashgoogle50.0M8.3M58.3M
48Qwen3.6-Plus (Together)together50.0M8.3M58.3M
49Llama 3.3 70B (Together)together28.4M28.4M56.8M
50DeepSeek V3.1 (Together)together41.7M14.7M56.4M
51Sonarperplexity25.0M25.0M50.0M
52Mixtral 8x22B (Together)together20.8M20.8M41.7M
53Qwen 2.5 72B (Together)together20.8M20.8M41.7M
54DeepSeek V3 (Together)together20.0M20.0M40.0M
55GPT-5.4 miniopenai33.3M5.6M38.9M
56Claude Haiku 4.5anthropic25.0M5.0M30.0M
57Grok 4.20xai20.0M10.0M30.0M
58Grok 4.3xai20.0M10.0M30.0M
59o4-miniopenai22.7M5.7M28.4M
60Qwen3.7-Max (Together)together20.0M6.7M26.7M
61Kimi K2.6 (Together)together20.8M5.6M26.4M
62GLM-5.1 (Together)together17.9M5.7M23.5M
63Gemini 2.5 Progoogle20.0M2.5M22.5M
64GPT-5openai20.0M2.5M22.5M
65GPT-5.1openai20.0M2.5M22.5M
66DeepSeek V4 Prodeepseek14.4M7.2M21.6M
67Mistral Medium 3.5mistral16.7M3.3M20.0M
68Gemini 3.5 Flashgoogle16.7M2.8M19.4M
69DeepSeek V4 Pro (Together)together11.9M5.7M17.6M
70Magistral Mediummistral12.5M5.0M17.5M
71Mixtral 8x22Bmistral12.5M4.2M16.7M
72Pixtral Largemistral12.5M4.2M16.7M
73GPT-5.2openai14.3M1.8M16.1M
74GPT-4.1openai12.5M3.1M15.6M
75o3openai12.5M3.1M15.6M
76Sonar Deep Researchperplexity12.5M3.1M15.6M
77Sonar Reasoning Properplexity12.5M3.1M15.6M
78Gemini 3 Progoogle12.5M2.1M14.6M
79Gemini 3.1 Progoogle12.5M2.1M14.6M
80Llama 3.1 405B (Together)together7.1M7.1M14.3M
81Command Acohere10.0M2.5M12.5M
82Command R+ 08-2024cohere10.0M2.5M12.5M
83GPT-4oopenai10.0M2.5M12.5M
84DeepSeek R1 (Together)together8.3M3.6M11.9M
85Gemini 2.5 Pro (>200k tokens)google10.0M1.7M11.7M
86GPT-5.4openai10.0M1.7M11.7M
87Mistral Large (Together)together8.3M2.8M11.1M
88Claude Sonnet 4anthropic8.3M1.7M10.0M
89Claude Sonnet 4.5anthropic8.3M1.7M10.0M
90Claude Sonnet 4.6anthropic8.3M1.7M10.0M
91Sonar Properplexity8.3M1.7M10.0M
92Claude Opus 4.5anthropic5.0M1.0M6.0M
93Claude Opus 4.6anthropic5.0M1.0M6.0M
94Claude Opus 4.7anthropic5.0M1.0M6.0M
95Claude Opus 4.8anthropic5.0M1.0M6.0M
96GPT-5.5openai5.0M833.3K5.8M
97Claude Opus 4anthropic1.7M333.3K2.0M
98Claude Opus 4.1anthropic1.7M333.3K2.0M
99GPT-5 Proopenai1.7M208.3K1.9M
100o3-proopenai1.3M312.5K1.6M
101GPT-5.2 Proopenai1.2M148.8K1.3M
102GPT-5.4 Proopenai833.3K138.9K972.2K
103GPT-5.5 Proopenai833.3K138.9K972.2K
103 models compared at $50.00/mo budget

How does this calculator work?

  1. Enter your monthly budget — the total dollar amount you want to spend on AI API calls per month.
  2. Optionally select a focus model — highlights that model in the table and shows a detailed breakdown.
  3. Choose a budget split — decide how to allocate between input and output tokens (50/50, 80/20, or 20/80).
  4. Compare the table — models are ranked from most tokens to least, so the best-value models appear first.

Methodology

Token allowance is calculated by inverting the standard cost formula:

input_tokens = (budget × split_ratio / input_rate_per_M) × 1,000,000

output_tokens = (budget × (1 - split_ratio) / output_rate_per_M) × 1,000,000

The budget split controls what fraction of your monthly spend goes toward input vs output tokens. For most chat use cases, 50/50 is a reasonable default. If you send long prompts with short replies, use 80/20. If you request long-form content generation, use 20/80.

All rates come from our daily-updated pricing database. Models with $0 rates (free tiers) are excluded from ranking.

Need AI-powered writing on a budget? Writesonic gives you unlimited AI writing features at a flat monthly rate — great if you want predictable costs without counting tokens.