Skip to main content

Model comparison

Claude Mythos 5 vs Ling 3.0 Flash FP8

Updated August 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Claude Mythos 5

Anthropic

83.0/100

Supported · Public rank #1

90% interval 79.3–86.8

Ling 3.0 Flash FP8

InclusionAI

Evidence status unavailable

90% interval unavailable

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 based on different benchmark sets are marked directional and do not name a winner.

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

Show secondary and unsupported calls
  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    No shared weighted benchmark basis supports a winner.

    Confidence: limited

  • Agentic work

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

    Not enough matched evidence

    No shared weighted benchmark basis supports a winner.

    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: listed-rates

  • 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
1
Claude Mythos 5 only
14
Ling 3.0 Flash FP8 only
3
Like-for-like categories
0 / 8

1 category uses different evidence sets. Those rows remain visible for coverage context but do not name a winner.

Category results, on a stated basis

Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.

Knowledge

Directional only
Claude Mythos 5
68.5
Ling 3.0 Flash FP8
84.0
Weighted basis
2 vs 1 rows
Reading
Directional only

Agentic

Not comparable
Claude Mythos 5
87.0
Ling 3.0 Flash FP8
Not measured
Weighted basis
3 vs 0 rows
Reading
Not comparable

Coding

Not comparable
Claude Mythos 5
89.7
Ling 3.0 Flash FP8
40.4
Weighted basis
2 vs 1 rows
Reading
Not comparable

Reasoning

Not comparable
Claude Mythos 5
Not measured
Ling 3.0 Flash FP8
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Math

Not comparable
Claude Mythos 5
97.6
Ling 3.0 Flash FP8
Not measured
Weighted basis
1 vs 0 rows
Reading
Not comparable

Multilingual

Not comparable
Claude Mythos 5
Not measured
Ling 3.0 Flash FP8
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multimodal

Not comparable
Claude Mythos 5
93.5
Ling 3.0 Flash FP8
Not measured
Weighted basis
1 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
Claude Mythos 5
Not measured
Ling 3.0 Flash FP8
73.4
Weighted basis
0 vs 1 rows
Reading
Not comparable

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.

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
Ling 3.0 Flash FP8
API rate not published
Fits in one request

Ling 3.0 Flash FP8 has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Claude Mythos 5
$0.65
Fits in one request
Ling 3.0 Flash FP8
API rate not published
Fits in one request

Ling 3.0 Flash FP8 has no comparable published API token rate.

Cache-heavy agent loop

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

Claude Mythos 5
$0.9
Fits in one request
Ling 3.0 Flash FP8
API rate not published
Fits in one request
Cached-input rate unavailable

Ling 3.0 Flash FP8 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.

Reasoning profile

Claude Mythos 5

Reasoning

Ling 3.0 Flash FP8

Reasoning

Weight access

Claude Mythos 5

Proprietary

Ling 3.0 Flash FP8

Open Weight

License

Claude Mythos 5

Proprietary

Ling 3.0 Flash FP8

Open Weight

Release date

Claude Mythos 5

2026-06-09

Ling 3.0 Flash FP8

2026-08-04

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
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Claude Mythos 5 has the larger documented window (1M).

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 evidence18 rows

Agentic

  • Terminal-Bench 2.0

    Claude Mythos 588%
    Source
    Ling 3.0 Flash FP8

    Not directly comparable

  • OSWorld-Verified

    Claude Mythos 585%
    Source
    Ling 3.0 Flash FP8

    Not directly comparable

  • BrowseComp

    Claude Mythos 588%
    Source
    Ling 3.0 Flash FP8

    Not directly comparable

  • ExploitGym

    Claude Mythos 517.5%
    Source
    Ling 3.0 Flash FP8

    Not directly comparable

Coding

  • SWE-bench Verified

    Claude Mythos 595.5%
    Source
    Ling 3.0 Flash FP8

    Not directly comparable

  • SWE-bench Pro

    Claude Mythos 580.3%
    Source
    Ling 3.0 Flash FP8

    Not directly comparable

  • Terminal-Bench 2.0

    Claude Mythos 588.0%
    Source
    Ling 3.0 Flash FP8

    Not directly comparable

  • SciCode

    Claude Mythos 5
    Ling 3.0 Flash FP840.4%
    Source

    Not directly comparable

Knowledge

  • GPQA

    Claude Mythos 594.1%
    Source
    Ling 3.0 Flash FP884%
    Source

    Claude Mythos 5 leads this result

  • HLE

    Claude Mythos 564.5%
    Source
    Ling 3.0 Flash FP8

    Not directly comparable

  • HLE w/o tools

    Claude Mythos 559%
    Source
    Ling 3.0 Flash FP8

    Not directly comparable

  • GPQA-D

    Claude Mythos 5
    Ling 3.0 Flash FP884.0%
    Source

    Not directly comparable

Math

  • USAMO 2026

    Claude Mythos 597.6%
    Source
    Ling 3.0 Flash FP8

    Not directly comparable

Multilingual

  • SWE Multilingual

    Claude Mythos 592.2%
    Source
    Ling 3.0 Flash FP8

    Not directly comparable

Multimodal

  • SWE-bench Multimodal

    Claude Mythos 554.9%
    Source
    Ling 3.0 Flash FP8

    Not directly comparable

  • CharXiv

    Claude Mythos 593.5%
    Source
    Ling 3.0 Flash FP8

    Not directly comparable

  • CharXiv w/o tools

    Claude Mythos 588.9%
    Source
    Ling 3.0 Flash FP8

    Not directly comparable

Instruction following

  • IFBench

    Claude Mythos 5
    Ling 3.0 Flash FP873.4%
    Source

    Not directly comparable

Frequently asked questions

Which is better, Claude Mythos 5 or Ling 3.0 Flash FP8?

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 Ling 3.0 Flash FP8?

The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.

Which is better for agentic tasks, Claude Mythos 5 or Ling 3.0 Flash FP8?

The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.

Which costs less, Claude Mythos 5 or Ling 3.0 Flash FP8?

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, Claude Mythos 5 or Ling 3.0 Flash FP8?

Claude Mythos 5 has the larger documented context window: 1M, compared with 262K.

Related comparisons

Last updated August 4, 2026

Watch Claude Mythos 5 vs Ling 3.0 Flash FP8

One weekly email when material rank, price, or benchmark evidence changes make this matchup worth revisiting.

Read a sample issue

Join 2,000+ readers.