gpt-5.3-codex vs kimi-k2
Side-by-side comparison of gpt-5.3-codex and kimi-k2: benchmarks, pricing, context window and capabilities. Both are accessible through Requesty's unified API. gpt-5.3-codex outperforms kimi-k2 on 4 of 5 shared benchmarks.
gpt-5.3-codex
Input / 1M
$1.75
Output / 1M
$14.00
Context
400K
Model ID
openai-responses/gpt-5.3-codex
kimi-k2
Input / 1M
$0.60
Output / 1M
$2.50
Context
262K
Model ID
vertex/kimi-k2
Benchmark comparison
Intelligence Indexreasoning
gpt-5.3-codex36.9%
kimi-k225.9%
Math Indexmath
gpt-5.3-codexN/A
kimi-k294.7%
GPQA Diamondreasoning
gpt-5.3-codex91.5%
kimi-k283.8%
AIME 2025math
gpt-5.3-codexN/A
kimi-k294.7%
LiveCodeBenchcoding
gpt-5.3-codexN/A
kimi-k285.3%
Terminal-Bench Hardagentic
gpt-5.3-codex53.0%
kimi-k231.1%
τ²-Benchagentic
gpt-5.3-codex86.0%
kimi-k293.0%
MMLU Proknowledge
gpt-5.3-codexN/A
kimi-k284.8%
Humanity's Last Examreasoning
gpt-5.3-codex42.5%
kimi-k223.8%
Scores sourced from official model cards, Artificial Analysis, and public leaderboards. Benchmarks measure specific skills and don't capture every aspect of model quality.
Pricing & specifications
| gpt-5.3-codex | kimi-k2 | |
|---|---|---|
| Input price / 1M | $1.75 | $0.60 |
| Output price / 1M | $14.00 | $2.50 |
| Context window | 400K tokens | 262K tokens |
| Max output | 128K tokens | 262K tokens |
| Vision input | Yes | N/A |
| Tool calling | Yes | Yes |
| Reasoning | Yes | Yes |
| Prompt caching | Yes | Yes |
| Computer use | N/A | N/A |
| Provider | OpenAI Responses | Google LLC (Vertex AI) |
Questions people ask
Is gpt-5.3-codex better than kimi-k2?
gpt-5.3-codex outperforms kimi-k2 on 4 of 5 shared benchmarks. See the benchmark comparison above for specifics: gpt-5.3-codex and kimi-k2 have different strengths across reasoning, coding, math and multimodal tasks.
Which is cheaper, gpt-5.3-codex or kimi-k2?
kimi-k2 is cheaper. gpt-5.3-codex costs $1.75/$14.00 per 1M input/output tokens, while kimi-k2 costs $0.60/$2.50.
Can I use gpt-5.3-codex and kimi-k2 through the same API?
Yes. Requesty provides a single OpenAI-compatible API that routes to both. Change just the "model" parameter to switch between "openai-responses/gpt-5.3-codex" and "vertex/kimi-k2", no other code changes needed.
What are the context windows?
gpt-5.3-codex supports up to 400K tokens of context. kimi-k2 supports up to 262K tokens. Longer context means you can feed larger documents or codebases in a single prompt, though quality often degrades past 128K for most models.
Switch between gpt-5.3-codex and kimi-k2 with one line of code
Requesty provides a single OpenAI-compatible API for 600+ models. Change the model parameter, not your code.