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BenchLM

GPT-5.4 Pro vs Hy-MT1.5-1.8B-1.25bit

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.

OpenAI logo
Model A
GPT-5.4 Pro

OpenAI

60.49/100

Estimated · Public rank #64

90% interval 49.0–72.0

Tencent Hunyuan logo
Model B
Hy-MT1.5-1.8B-1.25bit

Tencent Hunyuan

—

Evidence status unavailable

90% interval unavailable

Updated September 18, 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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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

    GPT-5.4 Pro

    GPT-5.4 Pro has the larger documented context window.

    Confidence: documented

Show secondary and unsupported calls

  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    GPT-5.4 Pro and Hy-MT1.5-1.8B-1.25bit 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

    Hy-MT1.5-1.8B-1.25bit is not ranked on the public lane for agentic, so no winner is named for agentic.

    Confidence: limited

  • Chat turn cost

    1K fresh input + 500 output tokens

    Not enough matched evidence

    A complete comparable API-rate estimate is not available for both models.

    Confidence: listed-rates

  • Cache-heavy agent loop cost

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

    Not enough matched evidence

    A complete comparable API-rate estimate is not available for both models.

    Confidence: rate-fallback

  • Repository review cost

    50K fresh input + 3K output tokens

    Not enough matched evidence

    A complete comparable API-rate estimate is not available for both models.

    Confidence: listed-rates

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-5.4 Pro only
10
Hy-MT1.5-1.8B-1.25bit only
0
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-5.4 Pro
56.4
Estimated · #35/154
Hy-MT1.5-1.8B-1.25bit
Not ranked
Basis
BenchAlign lane · 1 vs 0 public rows
Reading
Not comparable

Coding

Not comparable
GPT-5.4 Pro
Not ranked
Hy-MT1.5-1.8B-1.25bit
Not ranked
Basis
BenchAlign lane · 0 vs 0 public rows
Reading
Not comparable

Reasoning

Not comparable
GPT-5.4 Pro
70.2
Unranked · 2 rankable rows
Hy-MT1.5-1.8B-1.25bit
Not ranked
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Knowledge

Not comparable
GPT-5.4 Pro
59.0
Estimated · #39/184
Hy-MT1.5-1.8B-1.25bit
Not ranked
Basis
BenchAlign lane · 4 vs 0 public rows
Reading
Not comparable

Math

Not comparable
GPT-5.4 Pro
68.8
Unranked · 4 rankable rows
Hy-MT1.5-1.8B-1.25bit
Not ranked
Basis
Provisional lane · 2 vs 0 weighted rows
Reading
Not comparable

Multilingual

Not comparable
GPT-5.4 Pro
Not ranked
Hy-MT1.5-1.8B-1.25bit
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
GPT-5.4 Pro
Not ranked
Hy-MT1.5-1.8B-1.25bit
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
GPT-5.4 Pro
Not ranked
Hy-MT1.5-1.8B-1.25bit
Not ranked
Basis
Provisional lane · 0 vs 0 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-5.4 Pro
$0.12
Fits in one request
Hy-MT1.5-1.8B-1.25bit
API rate not published
Fits in one request

Hy-MT1.5-1.8B-1.25bit has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

GPT-5.4 Pro
$2.04
Fits in one request
Hy-MT1.5-1.8B-1.25bit
API rate not published
Fits in one request

Hy-MT1.5-1.8B-1.25bit has no comparable published API token rate.

Cache-heavy agent loop

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

GPT-5.4 Pro
$8.40
Fits in one request
Cached input priced at the published list-input rate
Hy-MT1.5-1.8B-1.25bit
API rate not published
Fits in one request
Cached-input rate unavailable

GPT-5.4 Pro has no published cached-input rate, so cached tokens use its listed input rate. Hy-MT1.5-1.8B-1.25bit has no comparable published API token rate.

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.

GPT-5.4 Pro

Not published

OpenAI pricing

Hy-MT1.5-1.8B-1.25bit

No comparable hosted API rate

Provider availability

GPT-5.4 Pro

Generally Available · OpenAI Responses API

OpenAI model catalog

Hy-MT1.5-1.8B-1.25bit

Not sourced

Reasoning profile

GPT-5.4 Pro

Reasoning

Hy-MT1.5-1.8B-1.25bit

Non-Reasoning

Weight access

GPT-5.4 Pro

Proprietary

Hy-MT1.5-1.8B-1.25bit

Open Weight

License

GPT-5.4 Pro

Proprietary

Hy-MT1.5-1.8B-1.25bit

Open Weight

Release date

GPT-5.4 Pro

2026-03-05

Hy-MT1.5-1.8B-1.25bit

2026-04-29

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
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
GPT-5.4 Pro has the larger documented window (1.05M).

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 evidence10 rows

Agentic

  • BrowseComp

    GPT-5.4 Pro89.3%
    Source
    Hy-MT1.5-1.8B-1.25bit—

    Not directly comparable

Reasoning

  • ARC-AGI-2

    GPT-5.4 Pro83.3%
    Source
    Hy-MT1.5-1.8B-1.25bit—

    Not directly comparable

Knowledge

  • HLE

    GPT-5.4 Pro58.7%
    Source
    Hy-MT1.5-1.8B-1.25bit—

    Not directly comparable

  • FrontierScience

    GPT-5.4 Pro36.7%
    Source
    Hy-MT1.5-1.8B-1.25bit—

    Not directly comparable

  • FrontierScience Research

    GPT-5.4 Pro36.7%
    Source
    Hy-MT1.5-1.8B-1.25bit—

    Not directly comparable

  • HLE w/o tools

    GPT-5.4 Pro42.7%
    Source
    Hy-MT1.5-1.8B-1.25bit—

    Not directly comparable

Math

  • IPhO 2025 (Theory)

    GPT-5.4 Pro93.5%
    Source
    Hy-MT1.5-1.8B-1.25bit—

    Not directly comparable

  • FrontierMath (legacy)

    GPT-5.4 Pro50%
    Source
    Hy-MT1.5-1.8B-1.25bit—

    Not directly comparable

  • FrontierMath v2 (Tiers 1-3)

    GPT-5.4 Pro50.000%
    Source
    Hy-MT1.5-1.8B-1.25bit—

    Not directly comparable

  • FrontierMath v2 (Tier 4)

    GPT-5.4 Pro37.500%
    Source
    Hy-MT1.5-1.8B-1.25bit—

    Not directly comparable

Questions

Which is better, GPT-5.4 Pro or Hy-MT1.5-1.8B-1.25bit?

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-5.4 Pro or Hy-MT1.5-1.8B-1.25bit?

GPT-5.4 Pro and Hy-MT1.5-1.8B-1.25bit are not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, GPT-5.4 Pro or Hy-MT1.5-1.8B-1.25bit?

Hy-MT1.5-1.8B-1.25bit is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, GPT-5.4 Pro or Hy-MT1.5-1.8B-1.25bit?

Both models do not have comparable published API token rates, so this page does not name a universal price winner.

Which has the larger context window, GPT-5.4 Pro or Hy-MT1.5-1.8B-1.25bit?

GPT-5.4 Pro has the larger documented context window: 1.05M, compared with 262K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated September 18, 2026

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