About Kimi K2.6

Kimi K2.6 is an open-source frontier model from Moonshot AI, released on April 20, 2026. It is a native multimodal agentic model built for long-horizon coding, autonomous execution, and swarm-based task orchestration. The model uses a Mixture-of-Experts (MoE) architecture with 1 trillion total parameters and 32 billion activated parameters per token, using 384 experts (8 selected plus 1 shared), 61 layers, and Multi-head Latent Attention (MLA). A 400M-parameter MoonViT vision encoder enables native image and video input processing.

Key specifications: 262,144-token context window, native INT4 quantization, and a 160K-token vocabulary. The model supports Thinking and Instant modes, compatible with vLLM, SGLang, and KTransformers inference engines, and exposes OpenAI and Anthropic-compatible APIs. Weights are available on Hugging Face under a Modified MIT license.

The most significant architectural advancement over K2.5 is the Agent Swarm system, which now scales to 300 sub-agents and 4,000 coordinated steps — up from 100 sub-agents and 1,500 steps. Benchmark improvements from K2.5 to K2.6 are concrete: SWE-Bench Pro moves from 50.7% to 58.6%, Terminal-Bench 2.0 from 50.8% to 66.7%, BrowseComp (Agent Swarm) from 78.4% to 86.3%, and Toolathlon from 27.8% to 50.0%.

Benchmark Performance

Coding and Software Engineering

Benchmark	Kimi K2.6 Score	Comparison
SWE-Bench Pro	58.6%	Ahead of GPT-5.4 (57.7%), Claude Opus 4.6 (53.4%), Gemini 3.1 Pro (54.2%)
SWE-Bench Verified	80.2%	—
Terminal-Bench 2.0	66.7%	Up from 50.8% on K2.5
LiveCodeBench v6	89.6%	—

Reasoning and Knowledge

Benchmark	Kimi K2.6 Score	Comparison
HLE-Full (with tools)	54.0%	Leads GPT-5.4 (52.1%), Claude Opus 4.6 (53.0%), Gemini 3.1 Pro (51.4%)
AIME 2026	96.4%	—
HMMT 2026	92.7%	—
GPQA-Diamond	90.5%	—

Agentic Search and Browsing

Benchmark	Kimi K2.6 Score	Comparison
BrowseComp (Agent Swarm)	86.3%	Up from 78.4% on K2.5
DeepSearchQA F1	92.5%	—

Kimi K2.6 is now available across 9 API providers. This analysis breaks down which one delivers the best performance, lowest cost, and fastest response times for your use case.

Kimi K2.6 API Review Summary

• 9 API providers benchmarked: Fireworks, Parasail, Kimi, Novita, Cloudflare, Together.ai (FP4), DeepInfra (FP4), SiliconFlow (FP8), Clarifai
• Most affordable (blended $/1M, 3:1 input:output): Parasail $1.15, DeepInfra (FP4) $1.44, Fireworks $1.71
• Lowest input token pricing: Parasail $0.60, DeepInfra (FP4) $0.75, Fireworks $0.95
• Lowest output token pricing: Parasail $2.80, DeepInfra (FP4) $3.50, Fireworks $4.00
• Fastest output speed: Clarifai 157.2 t/s, Fireworks 69.3 t/s, Cloudflare 67.1 t/s
• Lowest time to first token: Fireworks 0.71s, Together.ai (FP4) 0.72s, Clarifai 1.10s
• All 9 providers support JSON mode and function calling

Kimi K2.6 — Best APIs

Provider	Why it’s a best pick	Blended ($/1M)	Input ($/1M)	Output ($/1M)	Speed (t/s)	TTFT (s)	Context
DeepInfra (FP4)	#2 lowest blended price; strong for cost-sensitive workloads with private deployment support	$1.44	$0.75	$3.50	16	1.31s	262k
Parasail	Lowest cost across all metrics — blended, input, and output	$1.15	$0.60	$2.80	21	2.61s	262k
Fireworks	Best for low-latency interactive use; fastest first token with strong throughput	$1.71	$0.95	$4.00	69	0.71s	262k
Cloudflare	Strong throughput at competitive blended pricing	$1.71	—	—	67	1.82s	262k
Clarifai	Best for maximum throughput; fastest tokens/sec of all 9 providers	$1.71	—	—	157	1.10s	262k

Quick Verdict: Which Kimi K2.6 Provider is Best?

Based on benchmarks across 9 tracked providers, DeepInfra is the recommended API for cost-optimized production Kimi K2.6 deployment. At $1.44/1M blended tokens and $0.75/1M input tokens, it is the second-cheapest option overall and adds $0.15/1M cached-token pricing — a meaningful advantage for agentic workloads that resend large system prompts or persistent context repeatedly. It also supports private endpoint deployment, which matters once workloads grow past prototype scale.

For absolute lowest cost, Parasail leads at $1.15/1M blended. For lowest latency in interactive applications, Fireworks delivers the fastest time to first token at 0.71s. For maximum raw throughput, Clarifai leads at 157.2 t/s.

Overall Recommendation: DeepInfra (FP4)

DeepInfra offers the best balance of cost, deployment flexibility, and API features across all 9 benchmarked providers for Kimi K2.6.

• Output Speed: 16 t/s
• Time to First Token: 1.31s
• Blended Price: $1.44 / 1M tokens (#2 lowest)
• Input Price: $0.75 / 1M tokens
• Output Price: $3.50 / 1M tokens
• Cached Token Price: $0.15 / 1M tokens
• Context Window: 262k tokens
• API Features: JSON Mode + Function Calling — both supported
• Deployment: Public and private endpoints available

With 9 providers in the benchmark, the spread in pricing and throughput is real and decision-relevant. Parasail undercuts on raw token price but does not expose cached-token pricing — for agentic loops and repeated-context workloads, DeepInfra’s $0.15/1M cached rate can close that gap quickly. Clarifai and Fireworks lead on throughput but at higher token prices. DeepInfra’s combination of near-lowest cost, full API feature parity, and private deployment support makes it the most practical option for teams moving from development to production.

Start using Kimi K2.6 on DeepInfra →

Provider Analyses

1. Parasail — Lowest Cost Overall

• Output Speed: 21 t/s
• Time to First Token: 2.61s
• Blended Price: $1.15 / 1M tokens (lowest)
• Input Price: $0.60 / 1M tokens
• Output Price: $2.80 / 1M tokens
• Context Window: 262k tokens
• API Features: JSON Mode, Function Calling

Parasail is the cheapest entry point for Kimi K2.6 across every pricing metric — blended, input, and output. Its 2.61s TTFT is the highest of the top-5 providers, making it less suited for interactive applications, but for batch workloads or cost-first deployments where latency is not a constraint, it is the clear baseline to beat.

2. Fireworks — Best for Low-Latency Interactive Use

• Output Speed: 69.3 t/s
• Time to First Token: 0.71s (fastest)
• Blended Price: $1.71 / 1M tokens
• Input Price: $0.95 / 1M tokens
• Output Price: $4.00 / 1M tokens
• Context Window: 262k tokens
• API Features: JSON Mode, Function Calling

Fireworks posts the fastest time to first token at 0.71s and the second-highest output speed at 69.3 t/s, making it the right choice for interactive applications where perceived responsiveness matters. It is the only provider in the top tier that combines sub-second TTFT with strong throughput. The trade-off is token pricing: at $1.71/1M blended, it costs roughly 1.2x more than DeepInfra and 1.5x more than Parasail.

3. Clarifai — Best for Maximum Throughput

• Output Speed: 157.2 t/s (fastest)
• Time to First Token: 1.10s
• Blended Price: $1.71 / 1M tokens
• Context Window: 262k tokens
• API Features: JSON Mode, Function Calling

Clarifai leads all 9 providers on output speed at 157.2 t/s — more than twice the throughput of Fireworks and roughly 10x DeepInfra’s FP4 deployment. For batch processing, bulk code generation, or any workload where sustained generation speed is the primary constraint, Clarifai is the standout option. Its 1.10s TTFT is also competitive. Detailed per-token input/output pricing is not broken out in the benchmark data for Clarifai.

4. Cloudflare — Strong Throughput at Competitive Pricing

• Output Speed: 67.1 t/s
• Time to First Token: 1.82s
• Blended Price: $1.71 / 1M tokens
• Context Window: 262k tokens
• API Features: JSON Mode, Function Calling

Cloudflare delivers 67.1 t/s output speed — second only to Clarifai — at the $1.71/1M blended price tier. Its 1.82s TTFT is mid-pack. It is a solid choice for throughput-oriented workloads that also require the infrastructure and network advantages of Cloudflare’s edge platform. Detailed per-token input/output pricing is not broken out in the benchmark data.

5. Together.ai (FP4) — Lowest TTFT Runner-Up

• Time to First Token: 0.72s (#2 lowest)
• Context Window: 262k tokens
• API Features: JSON Mode, Function Calling

Together.ai posts the second-lowest time to first token at 0.72s, just behind Fireworks. It is a strong option for latency-sensitive interactive applications. Detailed pricing and throughput figures are not included in the benchmark data for the FP4 variant.

6. Kimi (Native API)

• Blended Price: $1.71 / 1M tokens
• Context Window: 262k tokens
• API Features: JSON Mode, Function Calling

Kimi’s native API provides first-party access to the model at a $1.71/1M blended price. It is the appropriate choice for teams that require direct access to the model creator for support, compliance, or contractual reasons. Detailed throughput and latency figures are not included in the current benchmark data.

7. Novita, SiliconFlow (FP8)

Novita and SiliconFlow (FP8) round out the provider list. Both support JSON mode and function calling. SiliconFlow FP8 is the most expensive tracked option at $2.15/1M blended. Neither has detailed per-token pricing broken out in the current benchmark data. Both serve as reasonable fallback options in routing setups.

Technical Deep-Dive: What Developers Need to Know

1. Throughput Dispersion Is Unusually Wide

With 9 providers, the spread in output speed is significant: Clarifai at 157.2 t/s versus DeepInfra FP4 at 16 t/s is nearly a 10x gap. This is driven by quantization (FP4 vs FP8 vs native INT4), hardware configuration, and serving optimization choices. DeepInfra’s FP4 deployment trades throughput for pricing efficiency and inference stability under load — the right tradeoff for most production agentic workloads where 16 t/s is more than sufficient. For batch processing where throughput is the primary constraint, Clarifai or Fireworks are the better routing targets.

2. Cached Token Pricing and Agentic Workloads

Kimi K2.6 is explicitly designed for long-horizon agentic workflows — multi-step orchestration, agent swarms, and persistent session state. These workloads typically resend the same system prompt, tool schemas, and orchestration instructions on every turn. DeepInfra is the only provider in this benchmark set that explicitly exposes cached-token pricing ($0.15/1M), which directly maps to cost savings for that usage pattern. For teams building agent loops or long-running coding copilots, this is a more meaningful differentiator than the raw blended price alone.

3. Thinking vs. Instant Mode

Kimi K2.6 supports two inference modes: Thinking mode (temperature 1.0, chain-of-thought reasoning) and Instant mode (temperature 0.6, direct responses). TTFT and output speed benchmarks here reflect standard generation; for Thinking mode workloads, the TTFT vs. first answer token distinction becomes relevant — similar to the dynamic seen with DeepSeek V4 Pro (Max). Teams using Thinking mode should benchmark end-to-end response time for their specific task type rather than relying on TTFT alone.

4. API Feature Parity Across All 9 Providers

All 9 providers support JSON mode and function calling. This means intelligent routing across providers — for example, directing throughput-heavy batch jobs to Clarifai while routing interactive requests to Fireworks — requires no application-level changes to handle structured outputs or tool calls.

FAQ

What is the cheapest Kimi K2.6 API provider?

Parasail has the lowest pricing across all metrics: $1.15/1M blended, $0.60/1M input, $2.80/1M output. DeepInfra (FP4) is the second-cheapest at $1.44/1M blended and adds cached-token pricing at $0.15/1M — which can make it the more cost-effective option for agentic workloads with repeated context.

Which provider has the fastest output speed?

Clarifai leads at 157.2 t/s. Fireworks is second at 69.3 t/s, followed by Cloudflare at 67.1 t/s. DeepInfra (FP4) benchmarks at 16 t/s due to its quantization approach.

Which provider has the lowest time to first token?

Fireworks leads at 0.71s, followed by Together.ai (FP4) at 0.72s and Clarifai at 1.10s.

Does DeepInfra support private deployment for Kimi K2.6?

Yes. DeepInfra supports both public and private endpoints for Kimi K2.6, making it the relevant option for teams that need dedicated compute or data isolation requirements beyond what a shared public endpoint provides.

What is the difference between Thinking and Instant mode?

Thinking mode enables chain-of-thought reasoning before generating a response (temperature 1.0) and is suited for complex reasoning tasks. Instant mode provides direct responses without intermediate reasoning (temperature 0.6, configured by passing {“thinking”: {“type”: “disabled”}} in the request body) and is suited for lower-latency interactive use cases.