Model comparison

GPT-4.1 Nano vs Solar Pro 3

OpenAI's GPT-4.1 Nano against Upstage's Solar Pro 3: vendor list prices, limits, abilities and the Artificial Analysis indexes side by side - and what OpenSmartRoute does when both are available.

CheaperGPT-4.1 Nano

GPT-4.1 Nano lists at $0.175 per million tokens blended against $0.262 for Solar Pro 3 - 1.5x less.

Intelligence: levelEven

Intelligence index 8 against 8: within a point of each other.

Stronger on codingSolar Pro 3

Solar Pro 3 scores 16 on the coding index against 11 - 5 points apart.

Longer contextGPT-4.1 Nano

GPT-4.1 Nano reads 1.0M tokens at once, Solar Pro 3 131k.

Abilities differEven

only GPT-4.1 Nano offers image input; only Solar Pro 3 offers reasoning.

NewerSolar Pro 3

Solar Pro 3 was released about 10 months later.

Side by side

Vendor list prices per million tokens and published limits; indexes are Artificial Analysis composites (0-100).

Specification	GPT-4.1 Nano	Solar Pro 3
Input price / 1M tokens	$0.10	$0.15
Output price / 1M tokens	$0.40	$0.60
Blended (3 in : 1 out)	$0.18	$0.26
Cached input / 1M	$0.03	$0.01
Context window	1.0M	131K
Max output	943K	118K
Input	image, text, file	text
Output	text	text
Tool calls
Structured output
Reasoning
Open weights
Intelligence index	8	8
Coding index	11	16
Agentic index	-	1
Released	Apr 14, 2025	Jan 27, 2026
Available on this deployment

What a month costs

List price times tokens for three typical workloads; your mix of input and output decides which model's pricing suits you.

Workload	GPT-4.1 Nano	Solar Pro 3	Difference
Support chat20M tokens in, 5M out a month - a help desk answering a few thousand conversations.	$4.00	$6.00	$2.00 less on GPT-4.1 Nano
Document summaries100M in, 5M out - long inputs, short answers.	$12.00	$18.00	$6.00 less on GPT-4.1 Nano
Coding assistant60M in, 20M out - a team's editor assistant, output-heavy.	$14.00	$21.00	$7.00 less on GPT-4.1 Nano

What the router does with the pair

The two measure the same on the intelligence index, so the router treats them as peers and lets price, observed latency and your outcomes decide: GPT-4.1 Nano wins on cost, and a few bad outcomes on either move the next requests to the other.

Price a request Playground

yaml

# targets.yaml - both models as routing targets (metadata.model links each to the catalogue entry)
targets:
  - { id: gpt-4.1-nano, kind: llm, metadata: { model: openai/gpt-4.1-nano } }
  - { id: solar-pro-3, kind: llm, metadata: { model: upstage/solar-pro-3 } }

# rules.yaml - the cheaper model by default, the stronger one when the request is hard
rules:
  - name: simple-requests-stay-cheap
    when: { max_complexity: 0.45 }
    prefer: [gpt-4.1-nano]
    weight: 0.8
  - name: hard-requests-escalate
    when: { min_complexity: 0.45 }
    prefer: [solar-pro-3]
    weight: 0.8

Frequently asked

Is GPT-4.1 Nano cheaper than Solar Pro 3?: Yes. GPT-4.1 Nano lists at $0.10 in / $0.40 out per million tokens, Solar Pro 3 at $0.15 in / $0.60 out; blended, GPT-4.1 Nano is the cheaper one.
Which is better, GPT-4.1 Nano or Solar Pro 3?: The two measure the same on the intelligence index, so the task, the price and the abilities decide.
Which has the longer context window?: GPT-4.1 Nano - 1.0M tokens against 131K.
Can I use GPT-4.1 Nano and Solar Pro 3 together?: Yes. Declare both as targets and OpenSmartRoute picks one per request on quality for the task, price and your rules - the cheaper model for the requests it can answer, the stronger one for the rest - and records why in the trace.

Also compared

Every OpenAI and Upstage model, with prices, is on the vendor pages; the rankings show what the router actually picks.

For the business

What it means for which models you pay for.

Catalogue of every vendor
The right model, not the famous one
Price, context, abilities and benchmark indexes side by side, with the model that fits each task named.
The rankings
89% less
Lower cost per request
On the 150-prompt benchmark the router spent 89% less than sending every prompt to the reference model, and the judged quality went up, not down.
Read the benchmark
Per million tokens, every model
Prices you can compare
The catalogue prints input and output prices and what three typical monthly workloads cost on each.
The model catalogue

Which LLM is the cheapest for our workload?: The best-for pages rank the live catalogue per task by the index that measures it, and the router picks the cheapest model that meets your quality rule for each request.
How much can we save on our LLM bill?: On the public benchmark the router saved 89% against sending everything to the reference model. Import last month's provider bill on the bill page and the estimate is computed on your own traffic before you change a line of code.
How often do model prices change?: The catalogue is refreshed from the vendors' price lists; each model page shows the date of its data.

Stop choosing between GPT-4.1 Nano and Solar Pro 3. Route to both.

Declare the pair as targets and OpenSmartRoute picks per request - the cheaper one where it holds up, the stronger one where it matters - with the comparison in every trace.

Create a free account Try a request

Free plan, no card. Fifteen thousand decisions a month with the full trace.

Specification

GPT-4.1 Nano

Solar Pro 3

Input price / 1M tokens

$0.10

$0.15

Output price / 1M tokens

$0.40

$0.60

Blended (3 in : 1 out)

$0.18

$0.26

Cached input / 1M

$0.03

$0.01

Context window

1.0M

131K

Max output

943K

118K

Input

image, text, file

text

Output

text

Tool calls

Structured output

Reasoning

Open weights

Intelligence index

Coding index

Agentic index

Released

Apr 14, 2025

Jan 27, 2026

Available on this deployment

Workload

GPT-4.1 Nano

Solar Pro 3

Difference

Support chat20M tokens in, 5M out a month - a help desk answering a few thousand conversations.

$4.00

$6.00

$2.00 less on GPT-4.1 Nano

Document summaries100M in, 5M out - long inputs, short answers.

$12.00

$18.00

$6.00 less on GPT-4.1 Nano

Coding assistant60M in, 20M out - a team's editor assistant, output-heavy.

$14.00

$21.00

$7.00 less on GPT-4.1 Nano

# targets.yaml - both models as routing targets (metadata.model links each to the catalogue entry) targets: - { id: gpt-4.1-nano, kind: llm, metadata: { model: openai/gpt-4.1-nano } } - { id: solar-pro-3, kind: llm, metadata: { model: upstage/solar-pro-3 } } # rules.yaml - the cheaper model by default, the stronger one when the request is hard rules: - name: simple-requests-stay-cheap when: { max_complexity: 0.45 } prefer: [gpt-4.1-nano] weight: 0.8 - name: hard-requests-escalate when: { min_complexity: 0.45 } prefer: [solar-pro-3] weight: 0.8

Frequently asked

Is GPT-4.1 Nano cheaper than Solar Pro 3?

Yes. GPT-4.1 Nano lists at $0.10 in / $0.40 out per million tokens, Solar Pro 3 at $0.15 in / $0.60 out; blended, GPT-4.1 Nano is the cheaper one.

Which is better, GPT-4.1 Nano or Solar Pro 3?

The two measure the same on the intelligence index, so the task, the price and the abilities decide.

Which has the longer context window?

GPT-4.1 Nano - 1.0M tokens against 131K.

Can I use GPT-4.1 Nano and Solar Pro 3 together?

Yes. Declare both as targets and OpenSmartRoute picks one per request on quality for the task, price and your rules - the cheaper model for the requests it can answer, the stronger one for the rest - and records why in the trace.

GPT-4.1 Nano vs Solar Pro 3

Side by side

What a month costs

What the router does with the pair

Frequently asked

Also compared

What it means for which models you pay for.

The right model, not the famous one

Lower cost per request

Prices you can compare

Stop choosing between GPT-4.1 Nano and Solar Pro 3. Route to both.

GPT-4.1 Nano vs Solar Pro 3

Side by side

What a month costs

What the router does with the pair

Frequently asked

Also compared

What it means for which models you pay for.

The right model, not the famous one

Lower cost per request

Prices you can compare

Stop choosing between GPT-4.1 Nano and Solar Pro 3. Route to both.