Model profile
Upstage
New in 2026

Upstage: Solar Pro 3

Upstage: Solar Pro 3 is a budget-priced text-first model from Upstage with partial runtime data, extended context posture, and the clearest fit around long-context research / agent workflows.

Best for: Long-context research / Agent workflowsN/A latencyExtended contextBudget pricing
Intelligence
25.9

Benchmark blend

Coding
13.3

Dev workflow signal

Context
128K Tokens

Extended

Input Price
$0.00

Budget tier

Decision snapshot
45

Upstage: Solar Pro 3 currently reads as a budget text-first option with extended context and a partially published runtime profile.

Overall profile
Use-case specific
Best for
Long-context research / Agent workflows
Latency tier
N/A
Price tier
Budget
Source coverage
OpenRouterArtificial Analysis

Decision Strip

Decision rail before the raw tables

Core buy-side signals stay in one pass. The rest of the page expands only after intelligence, speed, context, and price are clear.

Intelligence
25.9
26

General reasoning and benchmark headroom.

Limited
Speed
N/A
N/A

Latency data is partial.

Unavailable
Context
128K Tokens
76

How much prompt and task state can stay in view.

Competitive
Price
$0.00
86

$0.00 output / 1M

Efficient

Editorial Profile

Upstage: Solar Pro 3 in one narrative

Positioning, tradeoffs, and fit are consolidated into one read instead of repeating the same story across separate cards.

Use-case specificCoding score 13Math score N/A

Solar Pro 3 is Upstage's powerful Mixture-of-Experts (MoE) language model. With 102B total parameters and 12B active parameters per forward pass, it delivers exceptional performance while maintaining computational efficiency. Optimized...

Identity

Upstage text-first profile

Positioning

Long-context research / Agent workflows with extended context and partially published runtime.

Cost posture

Efficient spend profile. More comfortable for sustained prompt volume if the capability fit is right.

Strengths
  • Large context headroom supports repo-wide prompts and long research sessions.

Tradeoffs
  • Budget-friendly input pricing is a strength, but raw capability may vary by workload.

  • Latency data is incomplete, so interactive responsiveness is harder to rank confidently.

  • Current metadata points to a text-first profile rather than a broad multimodal one.

Best fit
  • Long-context summarization, repo analysis, and policy or document review.

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Intelligence
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Context
N/A
Input Price
$0.00
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Solar Pro 2 (Preview) (Reasoning)

Intelligence
18.8
Context
N/A
Input Price
$0.00
Upstage

Solar Pro 2 (Preview) (Non-reasoning)

Intelligence
16.0
Context
N/A
Input Price
$0.00

Benchmarks

Grouped by job-to-be-done

Only benchmark categories with actual signal are shown. Secondary values stay as simple definitions instead of nested micro-cards.

General intelligence

Broad reasoning, knowledge depth, and flagship benchmark posture.

Intelligence Index
25.9
GPQA
72.4%
HLE
10.1%
Coding

Software implementation, debugging quality, and coding benchmark signal.

Coding Index
13.3
SciCode
24.7%
Agent / tool use

Long-horizon execution quality and interactive benchmark evidence.

IFBench
71.2%
TAU2
86.3%
TerminalBench Hard
7.6%
LCR
27.0%

Specs & Pricing

Technical snapshot and cost posture

Specs stay neutral, pricing gets emphasis through values rather than extra containers. Raw provider internals remain in metadata at the end.

Technical snapshot
Context Window
128K Tokens
Vision
Text-first
Modalities
text
Tokenizer
Other
Moderation
No
Supported Parameters
include_reasoningmax_tokensreasoningresponse_formatstructured_outputstemperaturetool_choicetools
Input Modalities
text
Output Modalities
text
Price architecture
Input
per 1M input tokens
$0.00
Output
per 1M output tokens
$0.00
Blended
AA 3:1 mix
$0.00

This model is relatively efficient on price. It is the easier fit when sustained prompt volume matters.

OR Cache Read
$0.00

Metadata

Raw source tables at the end

Verification details remain available, but the page no longer forces them ahead of the editorial read.