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Proprietary model

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Released August 2026

Solar Pro 4: Intelligence, Performance & Price Analysis

Name: Intelligence
Creator: Artificial Analysis
License: https://artificialanalysis.ai/docs/legal/Terms-of-Use.pdf

Try it out

Available providers

Upstage

Performance

Time to first answer token 34.91sOutput speed 83 tok/s

62.4

Time per Intelligence Index task (minutes)

Cost

In $0.30Out $1.20Cache discount 80%

$0.96

Cost per Intelligence Index task

Verbosity

Input tokens 6.24BOutput/input 3.887%

243M

Output tokens from Intelligence Index

Solar Pro 4 is below average in intelligence and somewhat expensive when comparing to other models of similar price. It's also notably slow per task and very verbose. The model supports text input, outputs text, and has a 512k tokens context window with knowledge up to February 2026.

Solar Pro 4 scores 14 on the Artificial Analysis Intelligence Index, placing it below average among comparable models (median: 24). When evaluating the Intelligence Index, it generated 243M tokens, which is very verbose in comparison to the median of 107M.

Pricing for Solar Pro 4 is $0.30 per 1M input tokens (somewhat expensive, median: $0.24) and $1.20 per 1M output tokens (somewhat expensive, median: $0.83). On average, it costs $0.96 per task to evaluate Solar Pro 4 on the Intelligence Index.

At 62.4 minutes per Intelligence Index task, Solar Pro 4 is notably slow compared with the median of 7.4 minutes for comparable models (lower is better).

Reasoning	Yes
Input modality	Supports: text
Output modality	Supports: text
Knowledge cutoff	Feb 28, 2026
Context window	512k ~768 A4 pages of size 12 Arial font

Metrics are compared against models of the same class:

Non-reasoning models → compared only with other non-reasoning models
Reasoning models → compared across both reasoning and non-reasoning
Open weights models → compared only with other open weights models of the same size class:

Tiny: ≤4B parameters
Small: 4B–40B parameters
Medium: 40B–150B parameters
Large: >150B parameters

Proprietary models → compared across proprietary and open weights models of the same price range, using a blended 3:1 input/output price ratio:

<$0.15 per 1M tokens
$0.15–$1 per 1M tokens
>$1 per 1M tokens

Updated

Intelligence

Artificial Analysis Intelligence Index · Higher is better

No publicly available API

Time per Task

Inference time (minutes) per Intelligence Index task · Lower is better

No publicly available API

Cost per Task

Weighted average cost (USD) per Intelligence Index task · Lower is better

No publicly available API

IntelligenceUpdated

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index v5.0.1 incorporates 9 evaluations: AA-Briefcase v1.1, AutomationBench-AA, Terminal-Bench 4.0, FrontierCode-AA 2.0, AA-Omniscience v1.1, GDP.pdf, HLE-Diamond, CritPt v2 (Hard Subset), and Terminal-Bench-Science 0.1

Artificial Analysis Intelligence Index v5.0.1 includes: AA-Briefcase v1.1, AutomationBench-AA, Terminal-Bench 4.0, FrontierCode-AA 2.0, AA-Omniscience v1.1, GDP.pdf, HLE-Diamond, CritPt v2 (Hard Subset), Terminal-Bench-Science 0.1. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.

Artificial Analysis Intelligence Index by Open Weights / Proprietary

Indicates whether the model weights are available. Models are labelled as 'Commercial Use Restricted' if commercial use is limited by conditions, and as 'Non-commercial' if the license prohibits commercial use.

Intelligence Index vs. Cost per Task

Artificial Analysis Intelligence Index · Weighted average cost (USD) per Artificial Analysis Intelligence Index task

Most attractive quadrant

Pareto line

Weighted average cost per Intelligence Index task. Each evaluation’s cost is calculated from input, cache hit, cache write, reasoning, and answer token prices, divided by task count, and weighted by its Intelligence Index weight.

Capability Indexes

Measures the performance of models on specific capabilities and industries

Finance & Accounting Index

Incorporates 5 evaluations: AA-Briefcase v1.1, AA-Omniscience v1.1, HLE-Diamond, AutomationBench-AA, GDP.pdf · Higher is better

Strategy & Ops Index

Incorporates 4 evaluations: AutomationBench-AA, AA-Briefcase v1.1, AA-Omniscience v1.1, GDP.pdf · Higher is better

Legal Index

Incorporates 5 evaluations: AA-Omniscience v1.1, AA-Briefcase v1.1, HLE-Diamond, GDP.pdf, AutomationBench-AA · Higher is better

Engineering Index

Incorporates 7 evaluations: AA-Omniscience v1.1, CritPt v2 (Hard Subset), Terminal-Bench-Science 0.1, HLE-Diamond, Terminal-Bench 4.0, FrontierCode-AA 2.0, AA-Briefcase v1.1 · Higher is better

Economics Index

Incorporates 4 evaluations: AA-Omniscience v1.1, AA-Briefcase v1.1, HLE-Diamond, GDP.pdf · Higher is better

Benchmarks

Evaluations

Intelligence evaluations measured independently by Artificial Analysis · Higher is better

AA-Briefcase v1.1

Agentic knowledge work, Elo

AA-Omniscience v1.1 AccuracyUpdated

Knowledge

AA-Omniscience v1.1 Non-Hallucination RateUpdated

1 - hallucination rate

AutomationBench-AA

Agentic SaaS workflows

Terminal-Bench-Science 0.1New

Agentic scientific research workflows in a terminal

FrontierCode-AA 2.0New

Agentic software engineering in open-source repositories

HLE-DiamondNew

Reasoning & knowledge

GDP.pdf

Professional document reasoning, All-pass

Terminal-Bench 4.0

Agentic coding & terminal use

CritPt v2 (Hard Subset)

Physics reasoning

GDPval-AA v2.1

Agentic real-world work tasks, Elo

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

Cost

Cost per Intelligence Index Task

Weighted average cost (USD) per Intelligence Index task · Segmented by token type · Lower is better

Cost to Run Artificial Analysis Intelligence Index

Cost (USD) to run all evaluations in the Artificial Analysis Intelligence Index

The cost to run the evaluations in the Artificial Analysis Intelligence Index, calculated using the model's input, cache hit, cache write, reasoning, and answer token prices and the number of tokens used across evaluations (excluding repeats).

Pricing: Cache Hit, Input, and Output

Price (USD per M Tokens)

Price per token for cached prompts (previously processed), typically offering a significant discount compared to regular input price, represented as USD per million tokens. The values shown here are the cache hit price; cache write and cache storage are billed separately and vary by provider — see "Cache pricing by provider" for detail.

Performance

Measured by time per task (minutes), output speed (tokens per second), time to first answer token and time to first token (seconds)

Time per Intelligence Index Task

Output tokens divided by end-to-end output speed (minutes per Intelligence Index task) · Speed at the model's own endpoint or the median across providers · Lower is better

The weighted average time (minutes) per Artificial Analysis Intelligence Index task: output tokens per task divided by output speed, weighted by each benchmark's weight in the Intelligence Index.

Speed and latency metrics average each endpoint's runs over the past 5 days, and the error rate pools them. We run the benchmark every 6 hours, and endpoints of deprecated models every 18 hours.

Output Speed

Output tokens divided by total request time, including time to first token · Higher is better

Output tokens, including reasoning tokens, received per second over a request's full duration, from sending the request to receiving the final token. The headline value averages each Performance v3 workload over the past 5 days, then averages the workloads.

Time to First Answer Token

Seconds to first answer token received · Accounts for reasoning model 'thinking' time

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.

Token Use

Output Tokens per Intelligence Index Task

Weighted average number of output tokens used to run one task in the Artificial Analysis Intelligence Index

The number of tokens required per Intelligence Index task. This is calculated by multiplying the output tokens per eval by the relative weights of each benchmark in the Intelligence Index, then dividing by task count (excluding repeats).

Context Window

Context window: tokens limit · Higher is better

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).

Further details

								Weights
Solar Pro 4	Upstage	14	-	512k	$0.22	62.4	83	Not available

Frequently Asked Questions

Common questions about Solar Pro 4

Solar Pro 4 was released on August 6, 2026.

Solar Pro 4 was created by Upstage.

Solar Pro 4 scores 14 on the Artificial Analysis Intelligence Index, placing it below average among other models in a similar price tier (median: 24).

Solar Pro 4 takes 62.4 minutes per Intelligence Index task (based on Upstage's API), which is among the slowest compared to other models in a similar price tier (median: 7.4 minutes; lower is better).

Solar Pro 4 has a time to first answer token of 34.91s (based on Upstage's API), which is at the higher end compared to other models in a similar price tier (median: 8.81s).

Solar Pro 4 costs $0.30 per 1M input tokens (somewhat higher than average, median: $0.24) and $1.20 per 1M output tokens (somewhat higher than average, median: $0.83), based on Upstage's API.

Solar Pro 4 costs $0.30 per 1M input tokens and $1.20 per 1M output tokens (based on Upstage's API). For a blended rate (7:2:1 cache hit/input/output ratio), this is $0.22 per 1M tokens. Pricing may vary by provider. Compare provider pricing

When evaluated on the Intelligence Index, Solar Pro 4 generated 243M output tokens, which is at the higher end compared to other models in a similar price tier (median: 107M).

Yes, Solar Pro 4 is a reasoning model. It uses extended thinking or chain-of-thought reasoning to work through complex problems before providing an answer.

Solar Pro 4 supports text input.

Solar Pro 4 supports text output.

No, Solar Pro 4 does not support image input. It can only process text.

No, Solar Pro 4 is not multimodal. It only supports text input.

Solar Pro 4 has a context window of 512k tokens. This determines how much text and conversation history the model can process in a single request.

No, Solar Pro 4 is proprietary. The model weights are not publicly available.

Solar Pro 4 is a proprietary model and Upstage has not disclosed the model size or parameter count.

Solar Pro 4 achieves a score of 14 on the Artificial Analysis Intelligence Index. This composite benchmark evaluates models across knowledge work, coding, science, and general knowledge.

Solar Pro 4 has a knowledge cutoff of February 2026. The model's training data includes information up to this date.

Yes, Solar Pro 4 is available via API through 1 provider. Compare API providers

Solar Pro 4 is available through 1 API provider. Compare providers

Solar Pro 4: Intelligence, Performance & Price Analysis

Model summary

IntelligenceUpdated

Technical specifications

164 models in this class

IntelligenceUpdated

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index by Open Weights / Proprietary

Artificial Analysis Intelligence Index

Open Weights

Intelligence Index vs. Cost per Task

Cost per Intelligence Index Task

Artificial Analysis Intelligence Index

Capability Indexes

Evaluations

Intelligence Evaluation Relevance

Artificial Analysis Intelligence Index

Cost

Cost per Intelligence Index Task

Cost per Intelligence Index Task

Cost to Run Artificial Analysis Intelligence Index

Cost to Run Artificial Analysis Intelligence Index

Pricing: Cache Hit, Input, and Output

Cache Hit

Performance

Time per Intelligence Index Task

Time per Intelligence Index Task

Time Period

Output Speed

End-to-End Output Speed

Time to First Answer Token

Time to First Answer Token

Token Use

Output Tokens per Intelligence Index Task

Output Tokens per Intelligence Index Task

Context Window

Context Window

Context Window for RAG

Context Window

Further details

More from Upstage

Frequently Asked Questions

When was Solar Pro 4 released?

Who created Solar Pro 4?

How intelligent is Solar Pro 4?

How fast is Solar Pro 4?

What is the latency of Solar Pro 4?

How much does Solar Pro 4 cost?

What is Solar Pro 4 API pricing?

How verbose is Solar Pro 4?

Is Solar Pro 4 a reasoning model?

What input modalities does Solar Pro 4 support?

What output modalities does Solar Pro 4 support?

Can Solar Pro 4 process images?

Is Solar Pro 4 multimodal?

What is the context window of Solar Pro 4?

Is Solar Pro 4 open source?

How many parameters does Solar Pro 4 have?

How does Solar Pro 4 perform on benchmarks?

What is the knowledge cutoff date for Solar Pro 4?

Is Solar Pro 4 available via API?

Where can I use Solar Pro 4?