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Claude Mythos 5 vs o1-mini

Updated October 14, 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
Anthropic logo

Anthropic

—

Evidence status unavailable

90% interval unavailable

Model B
OpenAI logo

OpenAI

—

Evidence status unavailable

90% interval unavailable

Shared results
1
Claude Mythos 5 only
14
o1-mini only
6
Like-for-like categories
0 / 8

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

    Claude Mythos 5

    Claude Mythos 5 has the larger documented context window.

    Confidence: documented
  • Chat turn cost

    1K fresh input + 500 output tokens

    o1-mini

    o1-mini 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

    o1-mini

    o1-mini 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

    Claude Mythos 5 and o1-mini 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

    Claude Mythos 5 and o1-mini 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. o1-mini does not fit this workload in one request.

    Confidence: listed-rates

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.

—Claude Mythos 5—o1-mini

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
Claude Mythos 5
Not ranked
o1-mini
Not ranked
Basis
BenchAlign v5.8 lane · 4 vs 0 public rows
Reading
Not comparable

Coding

Not comparable
Claude Mythos 5
Not ranked
o1-mini
Not ranked
Basis
BenchAlign v5.8 lane · 3 vs 1 public rows
Reading
Not comparable

Reasoning

Not comparable
Claude Mythos 5
Not ranked
o1-mini
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Claude Mythos 5
89.7
Unranked · 3 rankable rows
o1-mini
Not ranked
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Knowledge

Not comparable
Claude Mythos 5
Not ranked
o1-mini
Not ranked
Basis
BenchAlign v5.8 lane · 3 vs 3 public rows
Reading
Not comparable

Multilingual

Not comparable
Claude Mythos 5
Not ranked
o1-mini
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Claude Mythos 5
Not ranked
o1-mini
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Claude Mythos 5
Not ranked
o1-mini
Not ranked
Basis
Provisional lane · 1 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 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.

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

Claude Mythos 5
$0.035
Fits in one request
o1-mini
$0.0033
Fits in one request

o1-mini has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Claude Mythos 5
$0.65
Fits in one request
o1-mini
$0.0682
Fits in one request

o1-mini has the lower modeled cost

Costs use the listed standard API rates.

Cache-heavy agent loop

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

Claude Mythos 5
$0.9
Fits in one request
o1-mini
$0.176
Does not fit in one request

o1-mini does not fit this workload in one request.

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.

Reasoning profile

Claude Mythos 5

Reasoning

o1-mini

Reasoning

Weight access

Claude Mythos 5

Proprietary

o1-mini

Proprietary

License

Claude Mythos 5

Proprietary

o1-mini

Proprietary

Release date

Claude Mythos 5

2026-06-09

o1-mini

2024-09-12

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: $0.65 vs $0.0682. Cache-heavy agent loop: $0.9 vs $0.176.
Context tradeoff
Claude Mythos 5 has the larger documented window (1M).
Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Claude Mythos 5 or o1-mini?

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, Claude Mythos 5 or o1-mini?

Claude Mythos 5 and o1-mini are not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, Claude Mythos 5 or o1-mini?

Claude Mythos 5 and o1-mini are not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, Claude Mythos 5 or o1-mini?

For the stated presets, chat costs $0.035 on Claude Mythos 5 and $0.0033 on o1-mini; repository review costs $0.65 and $0.0682; the cache-heavy agent loop costs $0.9 and $0.176. o1-mini does not fit this workload in one request.

Which has the larger context window, Claude Mythos 5 or o1-mini?

Claude Mythos 5 has the larger documented context window: 1M, compared with 128K.

Benchmark evidence

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

Browse raw public benchmark evidence21 rows

Agentic

  • Terminal-Bench 2.1

    Claude Mythos 588.0%
    Source
    o1-mini—

    Not directly comparable

  • OSWorld-Verified

    Claude Mythos 585%
    Source
    o1-mini—

    Not directly comparable

  • BrowseComp

    Claude Mythos 588%
    Source
    o1-mini—

    Not directly comparable

  • CyberGym

    Claude Mythos 583.8%
    Source
    o1-mini—

    Not directly comparable

Coding

  • SWE-bench Verified

    Claude Mythos 595.5%
    Source
    o1-mini—

    Not directly comparable

  • SWE-bench Pro

    Claude Mythos 580.3%
    Source
    o1-mini—

    Not directly comparable

  • Terminal-Bench 2.1

    Claude Mythos 588.0%
    Source
    o1-mini—

    Not directly comparable

  • HumanEval

    Claude Mythos 5—
    o1-mini92.4%
    Source

    Not directly comparable

Reasoning

  • DROP

    Claude Mythos 5—
    o1-mini83.9%
    Source

    Not directly comparable

Multimodal

  • SWE-bench Multimodal

    Claude Mythos 554.9%
    Source
    o1-mini—

    Not directly comparable

  • CharXiv

    Claude Mythos 593.5%
    Source
    o1-mini—

    Not directly comparable

  • CharXiv w/o tools

    Claude Mythos 588.9%
    Source
    o1-mini—

    Not directly comparable

Knowledge

  • GPQA

    Claude Mythos 594.1%
    Source
    o1-mini60%
    Source

    Claude Mythos 5 leads this result

  • HLE

    Claude Mythos 564.5%
    Source
    o1-mini—

    Not directly comparable

  • HLE w/o tools

    Claude Mythos 559%
    Source
    o1-mini—

    Not directly comparable

  • MMLU

    Claude Mythos 5—
    o1-mini85.2%
    Source

    Not directly comparable

  • SimpleQA

    Claude Mythos 5—
    o1-mini7.6%
    Source

    Not directly comparable

Multilingual

  • SWE Multilingual

    Claude Mythos 592.2%
    Source
    o1-mini—

    Not directly comparable

  • MGSM

    Claude Mythos 5—
    o1-mini89.9%
    Source

    Not directly comparable

Math

  • USAMO 2026

    Claude Mythos 597.6%
    Source
    o1-mini—

    Not directly comparable

  • MATH-500

    Claude Mythos 5—
    o1-mini90%
    Source

    Not directly comparable

21 public results · 1 shared

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Last updated October 14, 2026