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Model A
GPT-4o Audio

OpenAI

Evidence status unavailable

90% interval unavailable

GPT-4o Audio vs Solar Pro 3

Updated September 10, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Upstage logo
Model B
Solar Pro 3

Upstage

Evidence status unavailable

90% interval unavailable

Decision reading

The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. Use the documented cost, context, and runtime rows instead.

0 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

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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.

  • Chat turn cost

    1K fresh input + 500 output tokens

    Solar Pro 3

    Solar Pro 3 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 3

    Solar Pro 3 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

    GPT-4o Audio and Solar Pro 3 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

    GPT-4o Audio and Solar Pro 3 are not ranked on the public lane for agentic, so no winner is named for agentic.

    Confidence: limited

  • Long documents

    Prompts that approach the documented context limit

    No clear pick

    The documented context windows are equal.

    Confidence: documented

  • 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. GPT-4o Audio does not fit this workload in one request. Solar Pro 3 does not fit this workload in one request. GPT-4o Audio has no published cached-input rate, so cached tokens use its listed input rate. Solar Pro 3 has no published cached-input rate, so cached tokens use its listed input rate.

    Confidence: rate-fallback

What is actually comparable

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

Shared results
0
GPT-4o Audio only
0
Solar Pro 3 only
1
Like-for-like categories
0 / 8

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign 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
GPT-4o Audio
Not ranked
Solar Pro 3
Not ranked
Basis
BenchAlign lane · 0 vs 0 public rows
Reading
Not comparable

Coding

Not comparable
GPT-4o Audio
Not ranked
Solar Pro 3
Not ranked
Basis
BenchAlign lane · 0 vs 0 public rows
Reading
Not comparable

Reasoning

Not comparable
GPT-4o Audio
Not ranked
Solar Pro 3
43.2
Unranked · 2 rankable rows
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Knowledge

Not comparable
GPT-4o Audio
Not ranked
Solar Pro 3
Not ranked
Basis
BenchAlign lane · 0 vs 0 public rows
Reading
Not comparable

Math

Not comparable
GPT-4o Audio
Not ranked
Solar Pro 3
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multilingual

Not comparable
GPT-4o Audio
Not ranked
Solar Pro 3
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
GPT-4o Audio
Not ranked
Solar Pro 3
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
GPT-4o Audio
Not ranked
Solar Pro 3
87.1
#35/123
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) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

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.

A shared-evidence shape is not available.

BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.

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

GPT-4o Audio
$0.0075
Fits in one request
Solar Pro 3
$0.00045
Fits in one request

Solar Pro 3 has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

GPT-4o Audio
$0.155
Fits in one request
Solar Pro 3
$0.0093
Fits in one request

Solar Pro 3 has the lower modeled cost

Costs use the listed standard API rates.

Cache-heavy agent loop

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

GPT-4o Audio
$0.65
Does not fit in one request
Cached input priced at the published list-input rate
Solar Pro 3
$0.039
Does not fit in one request
Cached input priced at the published list-input rate

GPT-4o Audio does not fit this workload in one request. Solar Pro 3 does not fit this workload in one request. GPT-4o Audio has no published cached-input rate, so cached tokens use its listed input rate. Solar Pro 3 has no published cached-input rate, so cached tokens use its listed input rate.

Specification differences

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

Documented inputs

GPT-4o Audio

Not sourced

Solar Pro 3

Not sourced

Documented outputs

GPT-4o Audio

Not sourced

Solar Pro 3

Not sourced

Provider availability

GPT-4o Audio

Not sourced

Solar Pro 3

Not sourced

Reasoning profile

GPT-4o Audio

Non-Reasoning

Solar Pro 3

Reasoning

Weight access

GPT-4o Audio

Proprietary

Solar Pro 3

Proprietary

License

GPT-4o Audio

Proprietary

Solar Pro 3

Proprietary

Release date

GPT-4o Audio

Not sourced

Solar Pro 3

2026-01-26

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
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict.
Workload cost
Repository review: $0.155 vs $0.0093. Cache-heavy agent loop: $0.65 vs $0.039.
Context tradeoff
Both models list 128K.

Run the same representative tasks against both endpoints before changing production traffic.

Benchmark evidence

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

Browse raw public benchmark evidence1 rows

Instruction following

  • IFBench

    GPT-4o Audio
    Solar Pro 355.8%
    Source

    Not directly comparable

Frequently asked questions

Which is better, GPT-4o Audio or Solar Pro 3?

The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, GPT-4o Audio or Solar Pro 3?

GPT-4o Audio and Solar Pro 3 are not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, GPT-4o Audio or Solar Pro 3?

GPT-4o Audio and Solar Pro 3 are not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, GPT-4o Audio or Solar Pro 3?

For the stated presets, chat costs $0.0075 on GPT-4o Audio and $0.00045 on Solar Pro 3; repository review costs $0.155 and $0.0093; the cache-heavy agent loop costs $0.65 and $0.039. GPT-4o Audio does not fit this workload in one request. Solar Pro 3 does not fit this workload in one request. GPT-4o Audio has no published cached-input rate, so cached tokens use its listed input rate. Solar Pro 3 has no published cached-input rate, so cached tokens use its listed input rate.

Which has the larger context window, GPT-4o Audio or Solar Pro 3?

Both models list the same context window, 128K.

Related comparisons

Last updated September 10, 2026

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