Together AI: Models Intelligence, Performance & Price

Together AI
Together AI

Analysis of Together AI'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 Together AI for your use-case.

Most Intelligent

Updated
#1
GLM-5.2 (max)
GLM-5.2 (max)
51
#2
MiniMax-M3
MiniMax-M3
44
#3
DeepSeek V4 Pro (max)
DeepSeek V4 Pro (max)
44
#4
Kimi K2.6 (FP4)
Kimi K2.6 (FP4)
44
#5
Kimi K2.7 Code
Kimi K2.7 Code
42

Intelligence index

Total 18 models

Fastest

#1
gpt-oss-120b (low)
gpt-oss-120b (low)
581 t/s
#2
gpt-oss-120b (high)
gpt-oss-120b (high)
572 t/s
#3
GLM-5.2 (max)
GLM-5.2 (max)
478 t/s
#4
gpt-oss-20b (low)
gpt-oss-20b (low)
441 t/s
#5
gpt-oss-20b (high)
gpt-oss-20b (high)
414 t/s

Output speed

Total 18 models

Lowest Price

#1
Gemma 3n E4B
Gemma 3n E4B
$0.02
#2
gpt-oss-20b (high)
gpt-oss-20b (high)
$0.07
#3
gpt-oss-20b (low)
gpt-oss-20b (low)
$0.07
#4
Qwen3.5 9B (FP8)
Qwen3.5 9B (FP8)
$0.11
#5
gpt-oss-120b (high)
gpt-oss-120b (high)
$0.20

Blended price (per 1M tokens)

Total 18 models

Indicates a reasoning model

Together AI offers 18 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 Together AI are GLM-5.2 (max) (51), MiniMax-M3 (44), DeepSeek V4 Pro (max) (44).
  • For output speed, the fastest models are gpt-oss-120b (low) (581 t/s), gpt-oss-120b (high) (572 t/s), GLM-5.2 (max) (478 t/s).
  • For latency, Kimi K2.6 (FP4) (0.52s), Gemma 4 31B (FP8) (1.16s), Gemma 3n E4B (1.28s) offer the lowest time to first answer token.
  • For pricing, Gemma 3n E4B ($0.02), gpt-oss-20b (high) ($0.07), gpt-oss-20b (low) ($0.07) offer the lowest blended prices per 1M tokens. Prices vary up to 8.9x across models.
  • For context window size, MiniMax-M3 (1M), Nemotron 3 Ultra (512k), DeepSeek V4 Pro (max) (512k) support the largest context windows on Together AI.

Highlights

Updated
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 vs. Price

Blended at 7:2:1 (cache-input-output) · USD per 1M tokens (blended)
Most attractive quadrant
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.

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.

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).

The blended cache price 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).
  • 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
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 vs. Price

Blended at 7:2:1 (cache-input-output) · USD per 1M tokens (blended)
Most attractive quadrant
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.

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.

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).

The blended cache price 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).
  • 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 · USD per 1M tokens (blended)
Most attractive quadrant
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
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).

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 median (P50) measurement over the past 72 hours to reflect sustained changes in performance.

Further Analysis
Z AI logo
GLM-5.2 (max)
262k
Open
51
$0.90
478
1.06
6.29
4.18
MiniMax logo
MiniMax-M3
1M
Open
44
$0.22
92
0.82
27.87
21.64
DeepSeek logo
DeepSeek V4 Pro (max)
512k
Open
44
$1.00
330
1.00
15.76
13.24
Kimi logo
Kimi K2.6 (FP4)
262k
Open
44
$0.83
405
0.56
12.79
10.99
Kimi logo
Kimi K2.7 Code
262k
Open
42
$0.72
254
0.57
11.30
8.77
DeepSeek logo
DeepSeek V4 Pro (high)
512k
Open
41*
$1.00
319
1.01
8.82
6.25
MiniMax logo
MiniMax-M2.7
197k
Open
38
$0.22
150
0.55
20.24
16.36
NVIDIA logo
Nemotron 3 Ultra
512k
Open
38
$0.62
158
0.72
18.30
14.41
Kimi logo
Kimi K2.6 (FP4)
262k
Open
35*
$0.83
378
0.52
1.84
--
Z AI logo
GLM-4.7
203k
Open
34
$0.60
--
--
--
--
MiniMax logo
MiniMax-M2.5 (FP4)
197k
Open
34*
$0.22
--
--
--
--
Google logo
Gemma 4 31B
262k
Open
29
$0.23
59
1.16
38.85
29.26
Z AI logo
GLM-4.6
203k
Open
29
$0.76
--
--
--
--
Z AI logo
GLM-4.7
203k
Open
27*
$0.60
--
--
--
--
OpenAI logo
gpt-oss-120b (high)
131k
Open
24
$0.20
572
0.62
4.99
3.50
Z AI logo
GLM-4.6
203k
Open
23*
$0.76
--
--
--
--
Google logo
Gemma 4 31B (FP8)
262k
Open
22
$0.23
64
1.16
9.01
--
Alibaba logo
Qwen3.5 9B (FP8)
262k
Open
21
$0.11
71
0.70
35.68
27.98
ServiceNow logo
Apriel-v1.5-15B-Thinker
131k
Open
21*
$0.00
--
--
--
--
Alibaba logo
Qwen3 Coder Next (FP8)
262k
Open
21
$0.57
--
--
--
--
DeepSeek logo
DeepSeek V3.1
131k
Open
21*
$0.71
--
--
--
--
ServiceNow logo
Apriel-v1.6-15B-Thinker
131k
Open
21*
$0.00
--
--
--
--
DeepSeek logo
DeepSeek R1 0528
164k
Open
20*
$3.40
--
--
--
--
DeepSeek logo
DeepSeek R1 (Jan)
164k
Open
19
$3.40
--
--
--
--
Z AI logo
GLM-4.5-Air (FP8)
131k
Open
17*
$0.29
--
--
--
--
OpenAI logo
gpt-oss-120b (low)
131k
Open
15
$0.20
581
0.64
4.95
3.44
OpenAI logo
gpt-oss-20b (high)
131k
Open
15
$0.07
414
0.47
6.51
4.83
OpenAI logo
gpt-oss-20b (low)
131k
Open
14*
$0.07
441
0.40
6.07
4.53
Meta logo
Llama 4 Maverick
1.05M
Open
14
$0.33
--
--
--
--
Meta logo
Llama 3.3 70B Turbo
131k
Open
9
$0.88
78
1.47
7.89
--
Google logo
Gemma 3n E4B
32.8k
Open
1*
$0.02
62
1.28
9.30
--
Deep Cogito logo
Cogito v2.1
164k
Open
--
$1.25
--
--
--
--

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, 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).

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 Together AI

The most intelligent model available on Together AI is GLM-5.2 (max) with an Intelligence Index score of 51.

The fastest model on Together AI by output speed is gpt-oss-120b (low) at 580.8 tokens per second.

The model with the lowest time to first answer token on Together AI is Kimi K2.6 (FP4) at 0.52s. Lower latency means faster initial response time.

The most affordable model on Together AI by blended price is Gemma 3n E4B at $0.02 per 1M tokens (7:2:1 cache hit/input/output ratio).

Prices on Together AI vary up to 45x across models, from $0.02 per 1M tokens for Gemma 3n E4B to $1.00 per 1M tokens for DeepSeek V4 Pro (high).

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

Yes, all 18 models on Together AI support JSON mode for structured output.

17 of 18 models on Together AI support function calling (tool use).

Yes, Together AI offers 14 reasoning models: GLM-5.2 (max), MiniMax-M3, DeepSeek V4 Pro (max), Kimi K2.6 (FP4), Kimi K2.7 Code, DeepSeek V4 Pro (high), MiniMax-M2.7, Nemotron 3 Ultra, Gemma 4 31B, gpt-oss-120b (high), Qwen3.5 9B (FP8), gpt-oss-120b (low), gpt-oss-20b (high), and gpt-oss-20b (low). Reasoning models use extended thinking to work through complex problems before providing an answer.

Yes, all 18 models on Together AI 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 Together AI, 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.