GPT-5.4 vs Kimi K2 Thinking
GPT-5.4 (2026) and Kimi K2 Thinking (2025) are frontier-tier reasoning models from OpenAI and Moonshot AI. GPT-5.4 ships a 1.05m-token context window, while Kimi K2 Thinking ships a 256k-token context window. On pricing, GPT-5.4 ranges from $2.50 to $5/1M input tokens by tier; Kimi K2 Thinking costs $0.60/1M input tokens. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
GPT-5.4 fits 4x more tokens; pick it for long-context work and Kimi K2 Thinking for tighter calls.
Decision scorecard
Local evidence first| Signal | GPT-5.4 | Kimi K2 Thinking |
|---|---|---|
| Best for | reasoning-heavy apps, multimodal apps, and tool-calling agents | reasoning-heavy apps and provider-routed production |
| Decision fit | Coding, RAG, and Agents | RAG, Long context, and Classification |
| Context window | 1.05m | 256k |
| Cheapest output | $15/1M tokens | $2.50/1M tokens |
| Provider routes | 3 tracked | 7 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- GPT-5.4 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GPT-5.4 uniquely exposes Vision, Multimodal, and Function calling in local model data.
- Local decision data tags GPT-5.4 for Coding, RAG, and Agents.
- Kimi K2 Thinking has the lower cheapest tracked output price at $2.50/1M tokens.
- Kimi K2 Thinking has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Kimi K2 Thinking for RAG, Long context, and Classification.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
GPT-5.4
$5,750
Cheapest tracked route/tier: OpenAI API
Kimi K2 Thinking
$1,105
Cheapest tracked route/tier: Fireworks AI
Estimated monthly gap: $4,645. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter and Vercel AI Gateway; start route-level A/B tests there.
- Kimi K2 Thinking is $12.50/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision, Multimodal, and Function calling before moving production traffic.
- Provider overlap exists on OpenRouter and Vercel AI Gateway; start route-level A/B tests there.
- GPT-5.4 is $12.50/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- GPT-5.4 adds Vision, Multimodal, and Function calling in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-03-05 | 2025-01-01 |
| Context window | 1.05m | 256k |
| Parameters | — | 1T (32B active) |
| Architecture | decoder only | decoder only |
| License | Proprietary | MIT(OSI) |
| Openness | Proprietary | Open source |
| Commercial use | Commercial use with conditions | Commercial use allowed |
| Knowledge cutoff | 2025-08 | - |
Pricing and availability
| Pricing attribute | GPT-5.4 | Kimi K2 Thinking |
|---|---|---|
| Input price |
| $0.60/1M tokens |
| Output price |
| $2.50/1M tokens |
| Providers |
Capabilities
| Capability | GPT-5.4 | Kimi K2 Thinking |
|---|---|---|
| Vision | Yes | No |
| Multimodal | Yes | No |
| Reasoning | Yes | Yes |
| Function calling | Yes | No |
| Tool use | Yes | No |
| Structured outputs | Yes | Yes |
| Code execution | Yes | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on vision: GPT-5.4, multimodal input: GPT-5.4, function calling: GPT-5.4, tool use: GPT-5.4, and code execution: GPT-5.4. Both models share reasoning mode and structured outputs, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, GPT-5.4 lists tiered pricing: 0-272,000t is $2.50/1M input and $15/1M output; 272,000t+ is $5/1M input and $22.50/1M output, while Kimi K2 Thinking lists $0.60/1M input and $2.50/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Kimi K2 Thinking lower by about $5.08 per million blended tokens. For tiered rows, this cheapest-track view can understate interactive or fast-lane spend, so compare the tier you will actually use. Availability is 3 providers versus 7, so concentration risk also matters.
Choose GPT-5.4 when coding workflow support and larger context windows are central to the workload. Choose Kimi K2 Thinking when provider fit, lower input-token cost, and broader provider choice are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, GPT-5.4 or Kimi K2 Thinking?
GPT-5.4 supports 1.05m tokens, while Kimi K2 Thinking supports 256k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, GPT-5.4 or Kimi K2 Thinking?
GPT-5.4 lists tiered pricing: 0-272,000t is $2.50/1M input and $15/1M output; 272,000t+ is $5/1M input and $22.50/1M output. Kimi K2 Thinking lists $0.60/1M input and $2.50/1M output tokens on the cheapest tracked provider. Compare the tier you will actually use; cheap async pricing can overstate savings for interactive workflows. Provider discounts or batch pricing can still change the final bill.
Is GPT-5.4 or Kimi K2 Thinking open source?
GPT-5.4 is listed under Proprietary. Kimi K2 Thinking is listed under MIT. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for vision, GPT-5.4 or Kimi K2 Thinking?
GPT-5.4 has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, GPT-5.4 or Kimi K2 Thinking?
GPT-5.4 has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run GPT-5.4 and Kimi K2 Thinking?
GPT-5.4 is available on OpenAI API, OpenRouter, and Vercel AI Gateway. Kimi K2 Thinking is available on Fireworks AI, GCP Vertex AI, NVIDIA NIM, AWS Bedrock, and OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-06-04. Data sourced from public model cards and provider documentation.