AI Rate Card

Kimi K2.7 Code vs GLM-5.3: API price and specs

GLM-5.3 is 66% cheaper than Kimi K2.7 Code on input price.

GLM-5.3 is 75% cheaper than Kimi K2.7 Code on output price.

GLM-5.3 is 70% cheaper than Kimi K2.7 Code on a 1M-in / 200k-out workload.

GLM-5.3 has a 300% larger context than Kimi K2.7 Code.

FieldKimi K2.7 CodeGLM-5.3
Lowest input, per 1M$0.55 +190.3%$0.19
Median input, per 1M$0.95$1.40 +47.4%
Lowest output, per 1M$2.60 +306.2%$0.64
Median output, per 1M$4.00$4.40 +10%
Lowest unit price—$0.033 / request
Cost of 1M in + 200k out$1.07 +237%$0.32
Context262K +75%1M
Max output262K +75%1M
Providers46 +30.3%66
RegionsAPAC, EU, GLOBAL, USAPAC, EU, FI, GLOBAL, US
Acceptsapplication/pdf, file, image, image/bmp, image/gif, image/heic, image/heif, image/jpeg, image/png, image/webp, pdf, text, video, video/3gpp, video/avi, video/mov, video/mp4, video/mpeg, video/mpg, video/webm, video/wmv, video/x-flvfile, image, text
Returnstexttext
TypeText modelsText models
Free optionnoyes
Cheapest providerkenaritrustedrouter

Your own workload: how many tokens the model gets (input) and gives back (output) - for example, in a month. The "Cost" row of the table above is recalculated for these numbers, for each model.

Computed from current offers each time the page opens; the best value of a row is bold, the percent is how far behind the best.

Providers selling both

302ai, abacus, aiand, aihubmix, aiml, baseten, cloudflare-workers-ai, cometapi, cortecs, deepinfra, edenai, empiriolabs, fastrouter, huggingface, hyper, impossibl, inceptron, io-net, iteracompute, jiekou, kenari, kilo, meganova, melious, moark, nebius, novita, ofox, ollama, ollama-cloud, opencode, openrouter, orcarouter, perplexity-agent, poe, requesty, siliconflow, synthetic, tensorx, trustedrouter, vercel, zenmux

Frequently asked questions

Which is cheaper, Kimi K2.7 Code or GLM-5.3?

GLM-5.3 is 66% cheaper than Kimi K2.7 Code on input price. GLM-5.3 is 75% cheaper than Kimi K2.7 Code on output price. GLM-5.3 is 70% cheaper than Kimi K2.7 Code on a 1M-in / 200k-out workload.

Which has the larger context, Kimi K2.7 Code or GLM-5.3?

Kimi K2.7 Code: 262K tokens; GLM-5.3: 1M tokens.

Where can I use both Kimi K2.7 Code and GLM-5.3?

302ai, abacus, aiand, aihubmix, aiml, baseten, cloudflare-workers-ai, cometapi, cortecs, deepinfra, edenai, empiriolabs, fastrouter, huggingface, hyper, impossibl, inceptron, io-net, iteracompute, jiekou, kenari, kilo, meganova, melious, moark, nebius, novita, ofox, ollama, ollama-cloud, opencode, openrouter, orcarouter, perplexity-agent, poe, requesty, siliconflow, synthetic, tensorx, trustedrouter, vercel, zenmux