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o3-mini vs Solar Pro 4

Updated October 25, 2026. We do not rank this pair: at least one has no public score. Public scores include evidence status and uncertainty.

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Decision reading

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. 1 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A
OpenAI logo

OpenAI

39.55/100

Supported · Public rank #142

90% interval 27.6–51.5

Model B
Upstage logo

Upstage

—

Evidence status unavailable

90% interval unavailable

Shared results
1
o3-mini only
4
Solar Pro 4 only
9
Like-for-like categories
0 / 8
Supported: o3-miniHow the comparison works

Which one for your work

Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.

  • Long documents

    Prompts that approach the documented context limit

    Solar Pro 4

    Solar Pro 4 has the larger documented context window.

    Confidence: documented
  • Chat turn cost

    1K fresh input + 500 output tokens

    Solar Pro 4

    Solar Pro 4 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates
Show secondary and unsupported calls
  • Repository review cost

    50K fresh input + 3K output tokens

    Solar Pro 4

    Solar Pro 4 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates
  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    O3-mini and Solar Pro 4 are not ranked on the public lane for coding, so no winner is named for coding.

    Confidence: limited
  • Agentic work

    Tool use, computer use, and multi-step task completion

    Not enough matched evidence

    O3-mini and Solar Pro 4 are not ranked on the public lane for agentic, so no winner is named for agentic.

    Confidence: limited
  • Cache-heavy agent loop cost

    200K cached + 20K fresh input + 10K output tokens

    Not enough matched evidence

    The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. o3-mini does not fit this workload in one request. o3-mini has no published cached-input rate, so cached tokens use its listed input rate.

    Confidence: rate-fallback

Which one for a specific job

Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.

The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.

—o3-mini—Solar Pro 4

Not comparable · BenchAlign v5.8

The coding row is not comparable on the public lane: at least one model is not measured or not ranked there.

Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.

Same basis rules as the category table below

What is actually comparable

Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.

Shape of the matched evidence

Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.

Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.

Bars run 0–100 on each benchmark’s normalized display scale

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign v5.8 lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.

Agentic

Not comparable
o3-mini
Not ranked
Solar Pro 4
Not ranked
Basis
BenchAlign v5.8 lane · 0 vs 4 public rows
Reading
Not comparable

Coding

Not comparable
o3-mini
Not ranked
Solar Pro 4
Not ranked
Basis
BenchAlign v5.8 lane · 1 vs 3 public rows
Reading
Not comparable

Reasoning

Not comparable
o3-mini
Not ranked
Solar Pro 4
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
o3-mini
Not ranked
Solar Pro 4
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Knowledge

Not comparable
o3-mini
37.0
Supported · #129/187
Solar Pro 4
Not ranked
Basis
BenchAlign v5.8 lane · 2 vs 2 public rows
Reading
Not comparable

Multilingual

Not comparable
o3-mini
Not ranked
Solar Pro 4
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
o3-mini
Not ranked
Solar Pro 4
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
o3-mini
Not ranked
Solar Pro 4
Not ranked
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.8) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

Supported evidence per lane · bars run 0–100Methodology

What each workload costs

Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.

Chat turn

1K fresh input + 500 output tokens

o3-mini
$0.0033
Fits in one request
Solar Pro 4
$0.0009
Fits in one request

Solar Pro 4 has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

o3-mini
$0.0682
Fits in one request
Solar Pro 4
$0.0186
Fits in one request

Solar Pro 4 has the lower modeled cost

Costs use the listed standard API rates.

Cache-heavy agent loop

200K cached + 20K fresh input + 10K output tokens

o3-mini
$0.286
Does not fit in one request
Cached input priced at the published list-input rate
Solar Pro 4
$0.03
Fits in one request

o3-mini does not fit this workload in one request. o3-mini has no published cached-input rate, so cached tokens use its listed input rate.

Cached input falls back to the list input rate only where a cached rate is unpublished

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

o3-mini

Not published

Solar Pro 4

$0.06 per 1M cached input tokens

Upstage Solar Pro 4 launch post

Documented inputs

o3-mini

Not sourced

Solar Pro 4

Not sourced

Documented outputs

o3-mini

Not sourced

Solar Pro 4

Not sourced

Provider availability

o3-mini

Not sourced

Solar Pro 4

Not sourced

Reasoning profile

o3-mini

Reasoning

Solar Pro 4

Reasoning

Weight access

o3-mini

Proprietary

Solar Pro 4

Proprietary

License

o3-mini

Proprietary

Solar Pro 4

Proprietary

Release date

o3-mini

2025-01-31

Solar Pro 4

2026-08-11

If you already use one of these models

Deployment change
The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
Quality signal
At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
Workload cost
Repository review: $0.0682 vs $0.0186. Cache-heavy agent loop: $0.286 vs $0.03.
Context tradeoff
Solar Pro 4 has the larger documented window (512K).
Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, o3-mini or Solar Pro 4?

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, o3-mini or Solar Pro 4?

O3-mini and Solar Pro 4 are not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, o3-mini or Solar Pro 4?

O3-mini and Solar Pro 4 are not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, o3-mini or Solar Pro 4?

For the stated presets, chat costs $0.0033 on o3-mini and $0.0009 on Solar Pro 4; repository review costs $0.0682 and $0.0186; the cache-heavy agent loop costs $0.286 and $0.03. o3-mini does not fit this workload in one request. o3-mini has no published cached-input rate, so cached tokens use its listed input rate.

Which has the larger context window, o3-mini or Solar Pro 4?

Solar Pro 4 has the larger documented context window: 512K, compared with 200K.

Benchmark evidence

The full public result ledger is available for audit without forcing a wide desktop table onto a phone.

Browse raw public benchmark evidence14 rows

Agentic

  • Terminal-Bench 2.1

    o3-mini—
    Solar Pro 457.0%
    Source

    Not directly comparable

  • BrowseComp

    o3-mini—
    Solar Pro 449.2%
    Source

    Not directly comparable

  • MCP Atlas

    o3-mini—
    Solar Pro 461.4%
    Source

    Not directly comparable

  • APEX-Agents

    o3-mini—
    Solar Pro 418.7%
    Source

    Not directly comparable

Coding

  • SWE-bench Verified

    o3-mini49.3%
    Source
    Solar Pro 470.6%
    Source

    Solar Pro 4 leads this result

  • Terminal-Bench 2.1

    o3-mini—
    Solar Pro 457.0%
    Source

    Not directly comparable

  • LiveCodeBench

    o3-mini—
    Solar Pro 487.8%
    Source

    Not directly comparable

Knowledge

  • MMLU

    o3-mini86.9%
    Source
    Solar Pro 4—

    Not directly comparable

  • GPQA

    o3-mini77.2%
    Source
    Solar Pro 4—

    Not directly comparable

  • GPQA-D

    o3-mini—
    Solar Pro 489.0%
    Source

    Not directly comparable

  • MMLU-Pro

    o3-mini—
    Solar Pro 486.3%
    Source

    Not directly comparable

Instruction following

  • IFEval

    o3-mini93.9%
    Source
    Solar Pro 4—

    Not directly comparable

Math

  • AIME 2024

    o3-mini87.3%
    Source
    Solar Pro 4—

    Not directly comparable

  • AIME26

    o3-mini—
    Solar Pro 495.3%
    Source

    Not directly comparable

14 public results · 1 shared

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Last updated October 25, 2026