Modelflare vs IKunCode

One model on two relays: integrity, speed, price, cache and availability, plus intelligence adjusted for degradation and value for money, with advice for the priority you choose.

Model
claude-award
cc-kiro

Which to choose

Five dimensions

Further out is better. Integrity is the share of intelligence kept; the other four are places among all relays of this model.
IntegritySpeedPriceCacheNot checkedAvailability
ModelflareIKunCode

What matters most to you

For Balanced, choose Modelflare

Main reasons

Integrity25%

Modelflare keeps 100% of the model's intelligence; IKunCode keeps 34%

Availability20%

IKunCode was available 100.0% of the last 24 hours; Modelflare 97.7%

Value20%

Value: no data for at least one relay

Speed15%

Modelflare answers in 1.77 s, 38% faster than IKunCode at 2.88 s

Price15%

IKunCode costs ¥4.40 per session, 40% less than Modelflare at ¥7.30

Cache5%

Cache: no data for at least one relay

Modelflare

Stronger
Integrity100%Speed1.77 s
Weaker
Price¥7.30Availability97.7%

IKunCode

Stronger
Price¥4.40Availability100.0%
Weaker
Integrity34%Speed2.88 s

Key figures

Adjusted intelligence

Higher is better

Cost per coding session

2M input + 40k output tokens · Lower is better

Value for money

Intelligence points per ¥1 · Higher is better

All figures

Intelligence

Adjusted intelligence——
Intelligence kept100%34%
Question accuracy97% (90 questions)33% (18 questions)

Cost

Value for money——
Cost per coding session¥7.30¥4.40
Input price¥3.32¥2
Output price¥16.6¥10
Cache discountNot providedNot provided

Performance

Time to first token1.77 s2.88 s
Availability, last 24 hours97.7%100.0%
Samples13018

Route

Groupclaude-awardcc-kiro
Data securityLevel 4Level 0
Adjusted intelligence = the model's published intelligence index × intelligence kept. Intelligence kept = the relay's question accuracy ÷ the highest accuracy among checked relays of the same model; under 10 questions, no adjustment. Value = adjusted intelligence ÷ cost per coding session. Gaps under a threshold count as close. Advice weighs the metrics by the chosen priority and is a guide only.