Microsoft Azure: Models Intelligence, Performance & Price

Microsoft Azure
Microsoft Azure

Analysis of Microsoft Azure'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 Microsoft Azure for your use-case.

Most Intelligent

#1
Claude Fable 5 (with fallback)
Claude Fable 5 (with fallback)
60
#2
Claude Opus 4.7 (max)
Claude Opus 4.7 (max)
54
#3
Claude Sonnet 5 (max)
Claude Sonnet 5 (max)
53
#4
GPT-5.4 (xhigh)
GPT-5.4 (xhigh)
51
#5
Claude Sonnet 4.6 (max)
Claude Sonnet 4.6 (max)
47

Intelligence index

Total 68 models

Fastest

#1
gpt-oss-120b (low)
gpt-oss-120b (low)
336 t/s
#2
gpt-oss-120b (high)
gpt-oss-120b (high)
305 t/s
#3
GPT-4.1 nano
GPT-4.1 nano
273 t/s
#4
GPT-5.4 mini (xhigh)
GPT-5.4 mini (xhigh)
248 t/s
#5
Kimi K2.6
Kimi K2.6
242 t/s

Output speed

Total 68 models

Lowest Price

#1
GPT-5 nano (high)
GPT-5 nano (high)
$0.05
#2
GPT-5 nano (medium)
GPT-5 nano (medium)
$0.05
#3
GPT-4.1 nano
GPT-4.1 nano
$0.08
#4
GPT-4o mini
GPT-4o mini
$0.14
#5
gpt-oss-120b (high)
gpt-oss-120b (high)
$0.20

Blended price (per 1M tokens)

Total 68 models

Indicates a reasoning model

Azure offers 68 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 Azure are Claude Fable 5 (with fallback) (60), Claude Opus 4.7 (max) (54), and Claude Sonnet 5 (max) (53).
  • For output speed, the fastest models are gpt-oss-120b (low) (336 t/s), gpt-oss-120b (high) (305 t/s), and GPT-4.1 nano (273 t/s).
  • For latency, GPT-5.4 mini (0.74s), Phi-4 Multimodal (0.81s), and Phi-4 Mini (0.84s) offer the lowest time to first answer token.
  • For pricing, GPT-5 nano (high) ($0.05), GPT-5 nano (medium) ($0.05), and GPT-4.1 nano ($0.08) offer the lowest blended prices per 1M tokens. Prices vary up to 3.6x across models.
  • For context window size, GPT-5.4 (xhigh) (1M), Claude Fable 5 (with fallback) (1M), and Claude Opus 4.7 (max) (1M) support the largest context windows on Azure.

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.

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 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.

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

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).

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).

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).

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

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
Anthropic logo
Claude Fable 5 (with fallback)
1M
Proprietary
60
$10.17
72
121.72
128.63
--
Anthropic logo
Claude Opus 4.7 (max)
1M
Proprietary
54
$2.01
50
21.59
31.63
--
Anthropic logo
Claude Sonnet 5 (max)
1M
Proprietary
53
$1.64
85
211.31
217.18
--
OpenAI logo
GPT-5.4 (xhigh)
1.05M
Proprietary
51
$0.91
126
131.03
134.99
--
Anthropic logo
Claude Sonnet 4.6 (max)
200k
Proprietary
47
$1.27
64
112.57
120.44
--
DeepSeek logo
DeepSeek V4 Pro (max)
1M
Open
44
$0.90
90
1.46
55.58
48.57
Kimi logo
Kimi K2.6
262k
Open
44
$0.76
242
1.38
21.84
18.39
Anthropic logo
Claude Opus 4.6 (max)
1M
Proprietary
44*
--
43
16.36
27.95
--
DeepSeek logo
DeepSeek V4 Pro (high)
1M
Open
43
$0.94
89
1.51
29.54
22.41
OpenAI logo
GPT-5.2 (xhigh)
400k
Proprietary
42*
--
94
120.22
125.56
--
Anthropic logo
Claude Opus 4.5
200k
Proprietary
41*
--
51
15.68
25.50
--
OpenAI logo
GPT-5.2 Codex (xhigh)
400k
Proprietary
40*
--
150
99.94
103.28
--
OpenAI logo
GPT-5.4 mini (xhigh)
400k
Proprietary
40
$0.54
248
115.45
117.46
--
OpenAI logo
GPT-5.2 (medium)
400k
Proprietary
38*
--
82
7.27
13.35
--
Anthropic logo
Claude Opus 4.6 (high)
1M
Proprietary
38*
--
40
2.67
15.28
--
SpaceXAI logo
Grok 4.3 (high)
200k
Proprietary
38
$0.48
160
12.96
16.08
--
SpaceXAI logo
Grok 4.20 0309 v2
262k
Proprietary
37*
--
220
12.81
15.08
--
OpenAI logo
GPT-5.1 (high)
272k
Proprietary
37
$0.30
76
41.24
47.86
--
Anthropic logo
Claude 4.5 Sonnet
200k
Proprietary
36
$1.26
43
12.99
24.55
--
OpenAI logo
GPT-5 Codex (high)
400k
Proprietary
36*
--
160
9.25
12.38
--
SpaceXAI logo
Grok 4.3 (medium)
200k
Proprietary
36*
--
141
12.47
16.02
--
Anthropic logo
Claude Sonnet 4.6 (Non-reasoning)
200k
Proprietary
36*
--
44
1.94
13.27
--
SpaceXAI logo
Grok 4.3 (low)
200k
Proprietary
35*
--
143
5.83
9.32
--
Kimi logo
Kimi K2.5
262k
Open
35
$0.26
186
1.26
19.89
15.94
OpenAI logo
GPT-5.1 Codex (high)
400k
Proprietary
35*
--
111
18.59
23.10
--
OpenAI logo
GPT-5 (high)
400k
Proprietary
35
$0.24
81
61.64
67.83
--
Anthropic logo
Claude Opus 4.5
200k
Proprietary
35*
--
46
1.77
12.74
--
Kimi logo
Kimi K2.6
262k
Open
35*
--
180
1.73
4.51
--
OpenAI logo
GPT-5 (medium)
400k
Proprietary
34*
--
83
28.28
34.29
--
Anthropic logo
Claude 4.1 Opus
200k
Proprietary
34*
--
--
--
--
--
SpaceXAI logo
Grok 4
256k
Proprietary
33*
--
45
13.75
24.97
--
Kimi logo
Kimi K2 Thinking
256k
Open
33*
--
182
1.30
15.04
11.00
OpenAI logo
o3-pro
200k
Proprietary
33*
--
--
--
--
--
DeepSeek logo
DeepSeek V4 Pro
1M
Open
31*
--
89
1.57
7.18
--
OpenAI logo
GPT-5 (low)
400k
Proprietary
31*
--
82
7.51
13.63
--
OpenAI logo
GPT-5 mini (medium)
400k
Proprietary
31*
--
122
11.73
15.82
--
OpenAI logo
GPT-5.1 Codex mini (high)
400k
Proprietary
31*
--
162
20.43
23.52
--
OpenAI logo
o3
200k
Proprietary
30*
--
105
28.44
33.22
--
OpenAI logo
GPT-5.4 mini (medium)
400k
Proprietary
30*
--
159
12.96
16.11
--
Anthropic logo
Claude 4.5 Haiku
200k
Proprietary
30
$0.54
105
22.39
27.14
--
Kimi logo
Kimi K2.5
262k
Open
29*
--
180
1.28
4.05
--
Anthropic logo
Claude 4.5 Sonnet
200k
Proprietary
29*
--
41
1.87
14.06
--
Anthropic logo
Claude 4.1 Opus
200k
Proprietary
28*
--
--
--
--
--
SpaceXAI logo
Grok 4 Fast
2M
Proprietary
27*
--
--
--
--
--
OpenAI logo
GPT-5.2
400k
Proprietary
26*
--
77
1.13
7.64
--
OpenAI logo
o4-mini (high)
200k
Proprietary
26*
--
120
22.86
27.04
--
OpenAI logo
GPT-5 mini (high)
400k
Proprietary
25
$0.04
119
81.55
85.76
--
DeepSeek logo
DeepSeek V3.2
128k
Open
25*
--
176
1.93
4.77
--
OpenAI logo
gpt-oss-120b (high)
131k
Open
24
$0.08
305
1.53
9.73
6.56
Anthropic logo
Claude 4.5 Haiku
200k
Proprietary
24*
--
91
1.28
6.79
--
OpenAI logo
o1
200k
Proprietary
23*
--
--
--
--
--
SpaceXAI logo
Grok 3 mini Reasoning (high)
32k
Proprietary
23*
--
--
--
--
--
OpenAI logo
GPT-5.1
400k
Proprietary
20*
--
79
2.07
8.44
--
DeepSeek logo
DeepSeek R1 0528
128k
Open
20*
--
--
--
--
--
OpenAI logo
GPT-5 nano (high)
400k
Proprietary
20*
--
173
137.57
140.45
--
OpenAI logo
GPT-4.1
1M
Proprietary
19*
--
101
1.63
6.58
--
OpenAI logo
GPT-5 nano (medium)
400k
Proprietary
19*
--
137
55.10
58.74
--
OpenAI logo
o3-mini
200k
Proprietary
19*
--
211
7.82
10.19
--
DeepSeek logo
DeepSeek R1 (Jan)
128k
Open
19
$0.26
--
--
--
--
SpaceXAI logo
Grok 3
16k
Proprietary
18*
--
--
--
--
--
OpenAI logo
GPT-5 (minimal)
400k
Proprietary
17*
--
83
1.53
7.53
--
OpenAI logo
o1-preview
128k
Proprietary
17*
--
--
--
--
--
OpenAI logo
GPT-5.4 mini
400k
Proprietary
17*
--
189
0.74
3.38
--
SpaceXAI logo
Grok 4 Fast
2M
Proprietary
16*
--
--
--
--
--
Mistral logo
Mistral Large 3
256k
Open
16
$0.08
100
1.46
6.48
--
OpenAI logo
o3-mini (high)
200k
Proprietary
16
--
229
21.99
24.17
--
OpenAI logo
gpt-oss-120b (low)
131k
Open
15
$0.02
336
1.69
9.13
5.95
OpenAI logo
GPT-4.1 mini
1M
Proprietary
15
$0.06
108
1.35
5.97
--
Meta logo
Llama 4 Maverick (FP8)
128k
Open
14
$0.03
117
1.38
5.67
--
OpenAI logo
GPT-5 mini (minimal) East US 2 - Global Standard
400k
Proprietary
14*
--
--
--
--
--
Mistral logo
Mistral Medium 3
128k
Proprietary
12*
--
--
--
--
--
OpenAI logo
GPT-4o (Nov)
128k
Proprietary
11*
--
137
2.15
5.80
--
Meta logo
Llama 4 Scout
128k
Open
10
$0.01
--
--
--
--
OpenAI logo
GPT-4o (Aug)
128k
Proprietary
10*
--
141
1.35
4.91
--
OpenAI logo
GPT-4.1 nano
1M
Proprietary
10
$0.03
273
1.31
3.14
--
Meta logo
Llama 3.3 70B
128k
Open
9
$0.11
102
2.38
7.26
--
OpenAI logo
GPT-4o (May)
128k
Proprietary
9*
--
143
1.50
4.99
--
OpenAI logo
GPT-5 nano (minimal) East US 2 - Global Standard
400k
Proprietary
8*
--
--
--
--
--
OpenAI logo
GPT-4 Turbo
128k
Proprietary
8*
--
99
1.71
6.77
--
Cohere logo
Command A
256k
Open
8*
--
43
3.11
14.76
--
OpenAI logo
GPT-4o mini
128k
Proprietary
7*
--
89
1.69
7.33
--
Microsoft logo
Phi-4 Mini
128k
Open
6
$0.00
43
0.84
12.44
--
Microsoft logo
Phi-4
16.4k
Open
5*
--
--
--
--
--
Microsoft logo
Phi-4 Multimodal
128k
Open
5*
--
18
0.81
29.03
--

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 Microsoft Azure

The most intelligent model available on Microsoft Azure is Claude Fable 5 (with fallback) with an Intelligence Index score of 60.

The fastest model on Microsoft Azure by output speed is gpt-oss-120b (low) at 336.3 tokens per second.

The model with the lowest time to first answer token on Microsoft Azure is GPT-5.4 mini at 0.74s. Lower latency means faster initial response time.

The most affordable model on Microsoft Azure by blended price is GPT-5 nano (high) at $0.05 per 1M tokens (7:2:1 cache hit/input/output ratio).

Prices on Microsoft Azure vary up to 262x across models, from $0.05 per 1M tokens for GPT-5 nano (high) to $14.00 per 1M tokens for Claude Fable 5 (with fallback).

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

55 of 68 models on Microsoft Azure support JSON mode for structured output.

67 of 68 models on Microsoft Azure support function calling (tool use).

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 Microsoft Azure, 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.