DigitalOcean: Models Intelligence, Performance & Price

DigitalOcean
DigitalOcean

Analysis of DigitalOcean's models across key metrics including quality, price, output speed, latency, context window & more. This analysis is intended to support you in choosing the best model provided by DigitalOcean for your use-case.

Most Intelligent

#1
Qwen3.5 397B A17B
Qwen3.5 397B A17B
45
#2
MiniMax-M2.5
MiniMax-M2.5
42
#3
DeepSeek V3.2
DeepSeek V3.2
42
#4
Qwen3.5 397B A17B
Qwen3.5 397B A17B
40
#5
DeepSeek V3.2
DeepSeek V3.2
32

Intelligence index

Total 5 models

Fastest

#1
Qwen3.5 397B A17B
Qwen3.5 397B A17B
291 t/s
#2
MiniMax-M2.5
MiniMax-M2.5
269 t/s
#3
DeepSeek V3.2
DeepSeek V3.2
245 t/s
#4
DeepSeek V3.2
DeepSeek V3.2
245 t/s
#5
Qwen3.5 397B A17B
Qwen3.5 397B A17B
220 t/s

Output speed

Total 5 models

Lowest Price

#1
MiniMax-M2.5
MiniMax-M2.5
$0.52
#2
DeepSeek V3.2
DeepSeek V3.2
$0.78
#3
DeepSeek V3.2
DeepSeek V3.2
$0.78
#4
Qwen3.5 397B A17B
Qwen3.5 397B A17B
$1.29
#5
Qwen3.5 397B A17B
Qwen3.5 397B A17B
$1.29

Blended price (per 1M tokens, 3:1 input-output ratio)

Total 5 models

Indicates a reasoning model

DigitalOcean offers 5 models, each with different intelligence, performance, and pricing characteristics. Below is a comparison of the key metrics across models.

  • For intelligence, the top models on DigitalOcean are Qwen3.5 397B A17B (45), MiniMax-M2.5 (42), DeepSeek V3.2 (42).
  • For output speed, the fastest models are Qwen3.5 397B A17B (291 t/s), MiniMax-M2.5 (269 t/s), DeepSeek V3.2 (245 t/s).
  • For latency, MiniMax-M2.5 (0.65s), Qwen3.5 397B A17B (0.82s), DeepSeek V3.2 (0.93s) offer the lowest time to first token.
  • For pricing, MiniMax-M2.5 ($0.52), DeepSeek V3.2 ($0.78), DeepSeek V3.2 ($0.78) offer the lowest blended prices per 1M tokens. Prices vary up to 2.5x across models.
  • For context window size, Qwen3.5 397B A17B (262k), Qwen3.5 397B A17B (262k), MiniMax-M2.5 (197k) support the largest context windows on DigitalOcean.
  • Qwen3.5 397B A17B offers the best combination of intelligence and speed. For cost optimization, MiniMax-M2.5 provides the most competitive pricing.

Highlights

Intelligence
Artificial Analysis Intelligence Index · Higher is better
Speed
Output tokens per second · Higher is better
Price
USD per 1M tokens (3:1 input-output ratio) · Lower is better

Intelligence Evaluations

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index · Higher is better

Artificial Analysis Intelligence Index v4.0 includes: GDPval-AA, 𝜏²-Bench Telecom, Terminal-Bench Hard, SciCode, AA-LCR, AA-Omniscience, IFBench, Humanity's Last Exam, GPQA Diamond, CritPt. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.

Figures represent performance of the model's first-party API (e.g. OpenAI for o1) or the median across providers where a first-party API is not available (e.g. Meta's Llama models).

Intelligence Evaluations

Intelligence evaluations measured independently by Artificial Analysis · Higher is better
Results claimed by AI Lab (not yet independently verified)
GDPval-AA
Terminal-Bench Hard
𝜏²-Bench Telecom
AA-LCR
AA-Omniscience Accuracy
AA-Omniscience Non-Hallucination Rate
Humanity's Last Exam
GPQA Diamond
SciCode
IFBench
CritPt
APEX-Agents-AA
No data available
MMMU-Pro

Artificial Analysis Intelligence Index v4.0 includes: GDPval-AA, 𝜏²-Bench Telecom, Terminal-Bench Hard, SciCode, AA-LCR, AA-Omniscience, IFBench, Humanity's Last Exam, GPQA Diamond, CritPt. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.

Intelligence vs. Price

Blended at 7:2:1 (Cache Hit : Input : Output) · Artificial Analysis Intelligence Index · Price: USD per 1M tokens
Most attractive quadrant
Alibaba
DeepSeek
MiniMax

Artificial Analysis Intelligence Index v4.0 includes: GDPval-AA, 𝜏²-Bench Telecom, Terminal-Bench Hard, SciCode, AA-LCR, AA-Omniscience, IFBench, Humanity's Last Exam, GPQA Diamond, CritPt. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.

Price per token, represented as USD per million Tokens. Price is a blend of cache hit, input, and output token prices using the selected ratio.

The blended bar shown here uses cache hit price only. Other caching costs differ by provider:

  • Anthropic: charges a separate cache write fee, with different rates for 5-minute and 1-hour TTLs (1-hour TTL is more expensive). Blended price charts use Anthropic cache write price for the input leg.
  • Google (Vertex/Gemini): charges a per-hour cache storage fee in addition to cache hit pricing. Some providers also use tiered pricing for prompts above 200K tokens.
  • OpenAI, DeepSeek, others: typically charge only cache hit pricing with no write or storage fee.

See Prompt Caching for the full breakdown.

Figures represent performance of the model's first-party API (e.g. OpenAI for o1) or the median across providers where a first-party API is not available (e.g. Meta's Llama models).

Context Window

Context Window

Context window: tokens limit · Higher is better

Maximum number of combined input & output tokens. Output tokens commonly have a significantly lower limit (varied by model).

JSON Mode & Function Calling

Function (Tool) Calling & JSON Mode

ModelsFunction callingJSON Mode
Qwen3.5 397B A17B, DigitalOcean logoQwen3.5 397B A17B, DigitalOcean
MiniMax-M2.5, DigitalOcean logoMiniMax-M2.5, DigitalOcean
DeepSeek V3.2, DigitalOcean logoDeepSeek V3.2, DigitalOcean
Qwen3.5 397B A17B, DigitalOcean logoQwen3.5 397B A17B, DigitalOcean
DeepSeek V3.2, DigitalOcean logoDeepSeek V3.2, DigitalOcean

Indicates whether the provider supports function calling in their API. Function calling is also known as 'Tool Calling'.

Indicates whether the provider supports JSON mode in their API. When JSON mode is enabled, the models will always return a valid JSON object.

Pricing

Intelligence vs. Price

Blended at 7:2:1 (Cache Hit : Input : Output) · Artificial Analysis Intelligence Index · Price: USD per 1M tokens
Most attractive quadrant
Alibaba
DeepSeek
MiniMax

Artificial Analysis Intelligence Index v4.0 includes: GDPval-AA, 𝜏²-Bench Telecom, Terminal-Bench Hard, SciCode, AA-LCR, AA-Omniscience, IFBench, Humanity's Last Exam, GPQA Diamond, CritPt. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.

Price per token, represented as USD per million Tokens. Price is a blend of cache hit, input, and output token prices using the selected ratio.

The blended bar shown here uses cache hit price only. Other caching costs differ by provider:

  • Anthropic: charges a separate cache write fee, with different rates for 5-minute and 1-hour TTLs (1-hour TTL is more expensive). Blended price charts use Anthropic cache write price for the input leg.
  • Google (Vertex/Gemini): charges a per-hour cache storage fee in addition to cache hit pricing. Some providers also use tiered pricing for prompts above 200K tokens.
  • OpenAI, DeepSeek, others: typically charge only cache hit pricing with no write or storage fee.

See Prompt Caching for the full breakdown.

Figures represent performance of the model's first-party API (e.g. OpenAI for o1) or the median across providers where a first-party API is not available (e.g. Meta's Llama models).

Performance Summary

Output Speed vs. Price

Output speed: output tokens per second · Price: USD per 1M tokens · 10,000 Input Tokens
Most attractive quadrant
DigitalOcean

Tokens per second received while the model is generating tokens (ie. after first chunk has been received from the API for models which support streaming).

Price per token, represented as USD per million Tokens. Price is a blend of cache hit, input, and output token prices using the selected ratio.

Speed

Measured by Output Speed (tokens per second)

Output Speed

Output tokens per second · Higher is better · 10,000 Input Tokens

Tokens per second received while the model is generating tokens (ie. after first chunk has been received from the API for models which support streaming).

Figures represent performance of the model's first-party API (e.g. OpenAI for o1) or the median across providers where a first-party API is not available (e.g. Meta's Llama models).

Latency

Measured by Time (seconds) to First Token

Time to First Answer Token

Seconds to first token received · Lower is better
Input processing time
'Thinking' time (reasoning models, where applicable)

Time to first answer token received, in seconds, after API request sent. For reasoning models, this includes the 'thinking' time of the model before providing an answer. For models which do not support streaming, this represents time to receive the completion.

Seconds to receive a 500 token response. Key components:

  • Input time: Time to receive the first response token
  • Thinking time (only for reasoning models): Time reasoning models spend outputting tokens to reason prior to providing an answer. Amount of tokens based on the average reasoning tokens across a diverse set of 60 prompts (methodology details).
  • Answer time: Time to generate 500 output tokens, based on output speed

Figures represent performance of the model's first-party API (e.g. OpenAI for o1) or the median across providers where a first-party API is not available (e.g. Meta's Llama models).

End-to-End Response Time

Seconds to output 500 tokens, calculated based on time to first token, 'thinking' time for reasoning models, and output speed

End-to-End Response Time vs. Price

End-to-end response time: end-to-end seconds to output 500 tokens · Price: USD per 1M tokens
Most attractive quadrant
DigitalOcean

Seconds to receive a 500 token response considering input processing time, 'thinking' time of reasoning models, and output speed.

Price per token, represented as USD per million Tokens. Price is a blend of cache hit, input, and output token prices using the selected ratio.

Figures represent performance of the model's first-party API (e.g. OpenAI for o1) or the median across providers where a first-party API is not available (e.g. Meta's Llama models).

Key definitions

Maximum number of combined input & output tokens. Output tokens commonly have a significantly lower limit (varied by model).

Tokens per second received while the model is generating tokens (ie. after first chunk has been received from the API for models which support streaming).

Time to first token received, in seconds, after API request sent. For reasoning models which share reasoning tokens, this will be the first reasoning token. For models which do not support streaming, this represents time to receive the completion.

Price per token, represented as USD per million Tokens. Price is a blend of cache hit, input, and output token prices using the selected ratio.

Price per token generated by the model (received from the API), represented as USD per million Tokens.

Price per token included in the request/message sent to the API, represented as USD per million Tokens.

Metrics are 'live' and are based on the past 72 hours of measurements, measurements are taken 8 times a day for single requests and 2 times per day for parallel requests.

Frequently Asked Questions

Common questions about DigitalOcean

DigitalOcean offers 5 models that we track: Qwen3.5 397B A17B, MiniMax-M2.5, DeepSeek V3.2, Qwen3.5 397B A17B, and DeepSeek V3.2.

The most intelligent model available on DigitalOcean is Qwen3.5 397B A17B with an Intelligence Index score of 45.

The fastest model on DigitalOcean by output speed is Qwen3.5 397B A17B at 290.6 tokens per second.

The model with the lowest time to first token on DigitalOcean is MiniMax-M2.5 at 0.65s. Lower latency means faster initial response time.

The most affordable model on DigitalOcean by blended price is MiniMax-M2.5 at $0.52 per 1M tokens (3:1 input to output ratio).

Prices on DigitalOcean vary up to 2x across models, from $0.52 per 1M tokens for MiniMax-M2.5 to $1.29 per 1M tokens for Qwen3.5 397B A17B.

Yes, DigitalOcean offers an OpenAI-compatible API, making it easy to switch from OpenAI or use existing OpenAI SDK integrations.

Yes, all 5 models on DigitalOcean support JSON mode for structured output.

Yes, all 5 models on DigitalOcean support function calling (tool use).

Yes, DigitalOcean offers 3 reasoning models: Qwen3.5 397B A17B, MiniMax-M2.5, and DeepSeek V3.2. Reasoning models use extended thinking to work through complex problems before providing an answer.

Yes, all 5 models on DigitalOcean are open weight models.

Yes, provider performance can vary over time due to infrastructure changes, load balancing, and updates. We continuously benchmark all providers and display historical performance trends in the "Over Time" charts.

When choosing a model on DigitalOcean, consider: intelligence (for quality-sensitive tasks), output speed (for throughput-intensive tasks), latency (for interactive applications requiring quick first responses), pricing (for cost-sensitive workloads), and features like context window size, JSON mode, or function calling support.