Best Performance

Maximum benchmark performance.

A

Claude Fable 5 High

Anthropic
Arena score vs leader100%1551 Arena scoreThe leader is the 100% reference
API price
$10.00Input / 1M tokens
$50.00Output / 1M tokens
Choose this when the highest Arena score comes first.

Leads the supplied Arena coding comparison. Prioritize it for difficult generation, review and debugging workloads.

Best Value

A smarter performance-to-cost balance.

Z

GLM-5.3 Flash

Z.ai
Arena score vs leader98.3%1525 Arena scoreShare of the leader’s Arena score
Token cost savings
−99.4%Saves on input cost
$0.06Input / 1M tokens
−99.6%Saves on output cost
$0.20Output / 1M tokens
98.3% of the leader’s Arena score · 99.4% lower input cost · 99.6% lower output cost

A small supplied Arena coding score gap with lower input and output token prices for repeated developer workflows.

Arena · supplied snapshot·Supplied Arena snapshot · date pending·How we compare

Input and output savings use the separate supplied token rates. Combined cost uses 1M combined tokens: 75% input / 25% output; your workload mix changes the combined savings. Arena scores and prices are from the supplied snapshot. The leaderboard source and snapshot date still need confirmation.

Compare the essentials.

The same workload, with the details that help you choose.

Side-by-side comparison of recommended coding models
ComparisonClaude Fable 5 HighBest PerformanceGLM-5.3 FlashBest Value
Arena score1551

Supplied Arena snapshot · date pending

1525

Supplied Arena snapshot · date pending

Relative scorePerformance reference1.7% lower Arena score
Input / 1M tokens$10.00$0.06
Output / 1M tokens$50.00$0.20
Arena differencePerformance reference-26 / -1.7%
Cost differencePrice reference99.4% lower input cost · 99.6% lower output cost
Supported modalitiestext, image, document → texttext, image → text
Main reason to chooseChoose this when maximum benchmark performance matters more than inference cost.Consider this for production workloads where the reference price matters. Evaluate the benchmark gap against your own workload.
Best fitMaximum benchmark performance for reasoning, coding, visual understanding and documentsHigh-volume assistants, coding workflows and visual understanding
Billing detailsSupplied reference prices per 1M input and output tokens. No additional percentage discount is applied.Supplied reference prices per 1M input and output tokens. No additional percentage discount is applied.

Input and output savings use the separate supplied token rates. Combined cost uses 1M combined tokens: 75% input / 25% output; your workload mix changes the combined savings.

Implementation

Test your chosen model.

Copy a model test, replace the API key with your own, and run.

Copy the Python or cURL test for GLM-5.3 Flash. Replace the API-key placeholder with your own key and run.

Basic text test · Sends a basic text request. Vision input is not confirmed for this upstream model.

GLM-5.3 Flash · cURL
API_KEY='YOUR_ROTEN_API_KEY'

curl --fail-with-body --silent --show-error 'https://api.roten.ai/v1/chat/completions' \
  -H "Authorization: Bearer $API_KEY" \
  -H 'Content-Type: application/json' \
  --data '{
  "messages": [
    {
      "role": "user",
      "content": "Explain what an API key is in one short sentence."
    }
  ],
  "max_tokens": 128,
  "stream": false,
  "model": "glm-5.3-flash"
}'

Python tests use the standard library. Video cURL tests also use Python 3 to read task responses.

A clear reference point

Understand the recommendation.

Recommendations combine the supplied Arena scores with the supplied model prices. A benchmark score is one signal for choosing a model for your workload.

Arena · supplied snapshot·Supplied Arena snapshot · date pending·How we compare

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