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Model comparison

Claude Mythos 5 vs Ling 2.6 Flash

Data verified

Head-to-head evidence from 1 shared benchmark result across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.

83.93/100
Margin
40.1pts
← winning
InclusionAI
43.87/100
2 category wins0 category wins

Public leaderboard positions: Claude Mythos 5 #1 (Supported); Ling 2.6 Flash #154 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Claude Mythos 5 and Ling 2.6 Flash share 1 comparable benchmark result. 2 of 8 categories are comparable. 14 results are unique to Claude Mythos 5; 17 to Ling 2.6 Flash.

Updated July 23, 2026
Shared results
1
Claude Mythos 5 only
14
Ling 2.6 Flash only
17
Comparable categories
2 / 8

Pick Claude Mythos 5 if you want the stronger benchmark profile. Ling 2.6 Flash only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.

Confidence note. This is a partial-evidence comparison with 1 shared benchmark result across 1 evidence category; 2 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

Claude Mythos 5 is clearly ahead on the BenchAlign aggregate, 83.93 to 43.87. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

Claude Mythos 5's sharpest advantage is in coding, where it averages 89.7 against 27. The single biggest benchmark swing on the page is GPQA, 94.1% to 59%.

Claude Mythos 5 is the reasoning model in the pair, while Ling 2.6 Flash is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Claude Mythos 5 gives you the larger context window at 1M+, compared with 262K for Ling 2.6 Flash.

Category breakdown

Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.

Category scores and score margins for Claude Mythos 5 and Ling 2.6 Flash
CategoryClaude Mythos 5ΔLing 2.6 Flash
CodingClaude Mythos 589.7Margin 62.7Ling 2.6 Flash27.0
KnowledgeClaude Mythos 568.5Margin 9.5Ling 2.6 Flash59.0
AgenticClaude Mythos 587.0MarginNo overlapLing 2.6 FlashNot measured
MathClaude Mythos 597.6MarginNo overlapLing 2.6 FlashNot measured
MultimodalClaude Mythos 593.5MarginNo overlapLing 2.6 FlashNot measured
Inst. FollowingClaude Mythos 5Not measuredMarginNo overlapLing 2.6 Flash57.0

Decisive benchmark drivers

The largest measured benchmark gaps in this matchup, with exact reported values.

More
A · Claude Mythos 5B · Ling 2.6 Flash
  1. GPQA

    Knowledge
    Source ↗
    A 94.1%B 59%
    Winner: Claude Mythos 5Δ 35.1
    GPQA: Claude Mythos 5 scored 94.1%; Ling 2.6 Flash scored 59%. Claude Mythos 5 wins this benchmark.

Operational comparison

Runtime and commercial metrics are compared only when both models have a complete sourced value.

MetricClaude Mythos 5Ling 2.6 FlashComparison
Input / output priceUSD per 1M tokensClaude Mythos 5$10 input / $50 outputLing 2.6 FlashNot availableA complete price comparison is not available.
Generation speedtokens per secondClaude Mythos 5Not availableLing 2.6 Flash209.5 tok/sA complete speed comparison is not available.
First-answer latencyseconds to first tokenClaude Mythos 5Not availableLing 2.6 Flash1.07 sA complete latency comparison is not available.
Context windowmaximum listed tokensClaude Mythos 51M+Ling 2.6 Flash262KClaude Mythos 5 lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkClaude Mythos 5Ling 2.6 FlashResult
Terminal-Bench 2.0Source 88%Not comparable
OSWorld-VerifiedSource 85%Not comparable
BrowseCompSource 88%Not comparable
ExploitGymSource 17.5%Not comparable
τ²-bench resultsSource 86%Not comparable
GDPval-AASource 2.2%Not comparable
GDPval-AASource 545Not comparable
AA Agentic IndexSource 2.3%Not comparable
CodingClaude Mythos 5 wins
BenchmarkClaude Mythos 5Ling 2.6 FlashResult
SWE-bench VerifiedSource 95.5%Not comparable
SWE-bench ProSource 80.3%Not comparable
Terminal-Bench 2.0Source 88.0%Not comparable
SciCodeSource 27%Not comparable
AA Coding IndexSource 25.3%Not comparable
AA-SciCodeSource 27.1%Not comparable
Reasoning
BenchmarkClaude Mythos 5Ling 2.6 FlashResult
AA-LCRSource 25.0%Not comparable
CritPtSource 0.0%Not comparable
KnowledgeClaude Mythos 5 wins
BenchmarkClaude Mythos 5Ling 2.6 FlashResult
GPQASource 94.1%59%Claude Mythos 5 leads
HLESource 64.5%Not comparable
HLE w/o toolsSource 59%Not comparable
Artificial Analysis Intelligence IndexSource 14.1%Not comparable
AA-GPQA DiamondSource 59.3%Not comparable
AA-HLESource 6.2%Not comparable
AA-Omniscience IndexSource -65.7%Not comparable
AA-Omniscience AccuracySource 15.4%Not comparable
AA-Omniscience Hallucination RateSource 95.8%Not comparable
Math
BenchmarkClaude Mythos 5Ling 2.6 FlashResult
USAMO 2026Source 97.6%Not comparable
Multilingual
BenchmarkClaude Mythos 5Ling 2.6 FlashResult
SWE MultilingualSource 92.2%Not comparable
Multimodal
BenchmarkClaude Mythos 5Ling 2.6 FlashResult
SWE-bench MultimodalSource 54.9%Not comparable
CharXivSource 93.5%Not comparable
CharXiv w/o toolsSource 88.9%Not comparable
Inst. Following
BenchmarkClaude Mythos 5Ling 2.6 FlashResult
IFBenchSource 57%Not comparable
AA-IFBenchSource 57.4%Not comparable
Frequently Asked Questions (3)

Which is better, Claude Mythos 5 or Ling 2.6 Flash?

Claude Mythos 5 is ahead on BenchLM's BenchAlign leaderboard, 83.93 to 43.87. The biggest single separator in this matchup is GPQA, where the scores are 94.1% and 59%.

Which is better for knowledge tasks, Claude Mythos 5 or Ling 2.6 Flash?

Claude Mythos 5 has the edge for knowledge tasks in this comparison, averaging 68.5 versus 59. Inside this category, GPQA is the benchmark that creates the most daylight between them.

Which is better for coding, Claude Mythos 5 or Ling 2.6 Flash?

Claude Mythos 5 has the edge for coding in this comparison, averaging 89.7 versus 27. Ling 2.6 Flash stays close enough that the answer can still flip depending on your workload.

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Last updated: July 23, 2026

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