Makora: Models Intelligence, Performance & Price

Makora
Makora

Analysis of Makora'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 Makora for your use-case.

Most Intelligent

#1
Kimi K3 (max)
Kimi K3 (max)
57
#2
GLM-5.2 (max) (NVFP4)
GLM-5.2 (max) (NVFP4)
51
#3
DeepSeek V4 Pro (max)
DeepSeek V4 Pro (max)
44
#4
DeepSeek V4 Pro (high)
DeepSeek V4 Pro (high)
43
#5
DeepSeek V4 Flash (max)
DeepSeek V4 Flash (max)
40

Intelligence index

Total 10 models

Fastest

#1
DeepSeek V4 Flash (max)
DeepSeek V4 Flash (max)
284 t/s
#2
DeepSeek V4 Flash (high)
DeepSeek V4 Flash (high)
271 t/s
#3
DeepSeek V4 Flash
DeepSeek V4 Flash
241 t/s
#4
DeepSeek V4 Pro (max)
DeepSeek V4 Pro (max)
195 t/s
#5
DeepSeek V4 Pro (high)
DeepSeek V4 Pro (high)
171 t/s

Output speed

Total 10 models

Lowest Price

#1
Gemma 4 26B A4B
Gemma 4 26B A4B
$0.09
#2
Gemma 4 26B A4B
Gemma 4 26B A4B
$0.09
#3
DeepSeek V4 Flash (max)
DeepSeek V4 Flash (max)
$0.15
#4
DeepSeek V4 Flash (high)
DeepSeek V4 Flash (high)
$0.15
#5
DeepSeek V4 Flash
DeepSeek V4 Flash
$0.15

Blended price (per 1M tokens)

Total 10 models

Indicates a reasoning model

Makora offers 10 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 Makora are Kimi K3 (max) (57), GLM-5.2 (max) (NVFP4) (51), and DeepSeek V4 Pro (max) (44).
  • For output speed, the fastest models are DeepSeek V4 Flash (max) (284 t/s), DeepSeek V4 Flash (high) (271 t/s), and DeepSeek V4 Flash (241 t/s). Speed varies significantly across models, with a 66% difference between the fastest and slowest.
  • For latency, DeepSeek V4 Flash (0.67s), DeepSeek V4 Pro (0.99s), and Gemma 4 26B A4B (1.00s) offer the lowest time to first answer token.
  • For pricing, Gemma 4 26B A4B ($0.09), Gemma 4 26B A4B ($0.09), and DeepSeek V4 Flash (max) ($0.15) offer the lowest blended prices per 1M tokens.
  • For context window size, Kimi K3 (max) (1M), GLM-5.2 (max) (NVFP4) (1M), and DeepSeek V4 Pro (max) (1M) support the largest context windows on Makora.

Highlights

Artificial Analysis Intelligence Index · Higher is better
Output tokens per second · Higher is better
USD per 1M tokens (blended) · Lower is better

Intelligence Evaluations

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index v4.1 incorporates 9 evaluations: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR
Estimate (independent evaluation forthcoming)
Reasoning models are indicated by a lightbulb icon

Artificial Analysis Intelligence Index v4.1 includes: GDPval-AA v2, 𝜏³-Banking, Terminal-Bench v2.1, SciCode, Humanity's Last Exam, GPQA Diamond, CritPt, AA-Omniscience, AA-LCR. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.

Intelligence Evaluations

Intelligence evaluations measured independently by Artificial Analysis · Higher is better

Agentic real-world work tasks, (Elo-500)/2000

Agentic tool use

Agentic coding & terminal use

Coding

Reasoning & knowledge

Scientific reasoning

Physics reasoning

Long context reasoning

Agentic knowledge work, Elo

Agentic SaaS workflows

Legal agentic work, criterion pass rate

Agentic business operations

Instruction following

Long-horizon agentic tasks

Kubernetes incident root-cause analysis

Visual reasoning

Reasoning models are indicated by a lightbulb icon

While model intelligence generally translates across use cases, specific evaluations may be more relevant for certain use cases.

Intelligence Index vs. Price

Blended at 7:2:1 (cache-input-output) · USD per 1M tokens (blended)
Most attractive quadrant
Pareto line
Reasoning models are indicated by a lightbulb icon

While higher intelligence models are typically more expensive, they do not all follow the same price-quality curve.

Context Window

Context Window

Context window: tokens limit · Higher is better
Reasoning models are indicated by a lightbulb icon

Larger context windows are relevant to RAG (Retrieval Augmented Generation) LLM workflows which typically involve reasoning and information retrieval of large amounts of data.

Pricing

Intelligence Index vs. Price

Blended at 7:2:1 (cache-input-output) · USD per 1M tokens (blended)
Most attractive quadrant
Pareto line
Reasoning models are indicated by a lightbulb icon

While higher intelligence models are typically more expensive, they do not all follow the same price-quality curve.

Performance Summary

Output Speed vs. Price

Output speed: output tokens per second · USD per 1M tokens (blended)
Most attractive quadrant
Pareto line
Reasoning models are indicated by a lightbulb icon

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).

Speed

Measured by Output Speed (tokens per second)

Output Speed

Output tokens per second · Higher is better
Reasoning models are indicated by a lightbulb icon

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).

Latency

Measured by Time (seconds) to First Token

Latency: Time To First Answer Token

Seconds to first answer token received · Accounts for reasoning model 'thinking' time
Reasoning models are indicated by a lightbulb icon

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.

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 · USD per 1M tokens (blended)
Most attractive quadrant
Pareto line
Reasoning models are indicated by a lightbulb icon

Price per token, shown in USD per million tokens. Price is a blend of cache hit, input, and output token prices using the selected ratio (default 7:2:1 cache-input-output).

Further Analysis
Kimi logo
Kimi K3 (max)
1.05M
Open
57
$0.67
137
1.39
19.63
14.59
Z AI logo
GLM-5.2 (max) (NVFP4)
1M
Open
51
$0.51
146
0.88
18.04
13.73
DeepSeek logo
DeepSeek V4 Pro (max)
1M
Open
44
$0.76
195
0.92
25.97
22.48
DeepSeek logo
DeepSeek V4 Pro (high)
1M
Open
43
$0.78
171
0.93
15.48
11.63
DeepSeek logo
DeepSeek V4 Flash (max)
1M
Open
40
$0.15
284
0.70
22.20
19.74
DeepSeek logo
DeepSeek V4 Flash (high)
1M
Open
37
$0.11
271
0.64
7.06
4.57
DeepSeek logo
DeepSeek V4 Pro
1M
Open
31*
--
137
0.99
4.65
--
DeepSeek logo
DeepSeek V4 Flash
1M
Open
29*
--
241
0.67
2.75
--
Google logo
Gemma 4 26B A4B
1M
Open
26
$0.02
165
0.98
16.09
12.09
Google logo
Gemma 4 26B A4B
1M
Open
20*
--
170
1.00
3.94
--

Key definitions

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

Frequently Asked Questions

Common questions about Makora

The most intelligent model available on Makora is Kimi K3 (max) with an Intelligence Index score of 57.

The fastest model on Makora by output speed is DeepSeek V4 Flash (max) at 284.4 tokens per second.

The model with the lowest time to first answer token on Makora is DeepSeek V4 Flash at 0.67s. Lower latency means faster initial response time.

The most affordable model on Makora by blended price is Gemma 4 26B A4B at $0.09 per 1M tokens (7:2:1 cache hit/input/output ratio).

Prices on Makora vary up to 25x across models, from $0.09 per 1M tokens for Gemma 4 26B A4B to $2.31 per 1M tokens for Kimi K3 (max).

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

Yes, all 10 models on Makora support JSON mode for structured output.

Yes, all 10 models on Makora support function calling (tool use).

Yes, Makora offers 7 reasoning models: Kimi K3 (max), GLM-5.2 (max) (NVFP4), DeepSeek V4 Pro (max), DeepSeek V4 Pro (high), DeepSeek V4 Flash (max), DeepSeek V4 Flash (high), and Gemma 4 26B A4B. Reasoning models use extended thinking to work through complex problems before providing an answer.

Yes, all 10 models on Makora 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 Makora, 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.