Claude Haiku 5.5 vs Kimi K3
Anthropic · US | Moonshot AI · China · Updated June 2026
Quick verdict
Pick Claude Haiku 5.5 for 5x the context window of haiku 4.5 (1m vs 200k tokens) and double the max output (128k vs 64k) or first haiku-class model with an adjustable 'effort' setting to trade off cost, latency, and intelligence. Pick Kimi K3 for largest open-weight model at release — 2.8t sparse moe, self-hostable or 1m-token context with native vision (text, image and video). Choose Kimi K3 if you need self-hosting or data privacy; Claude Haiku 5.5 if you want a managed API.
Claude Haiku 5.5 (Anthropic, US) and Kimi K3 (Moonshot AI, China) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. Claude Haiku 5.5 is anthropic's October 7, 2026 small-model refresh — a 1M-token context window (up from 200K) at roughly 75% lower average cost than Haiku 4.5, priced at $0.10/$0.50 per million tokens. Kimi K3 is moonshot's 2.8-trillion-parameter open-weight model — the largest open AI at release, with a 1M context and strong self-reported coding scores. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
- ▸Price: Claude Haiku 5.5 is about 30× cheaper on input ($0.1/$0.5 per 1M tokens vs $3/$15 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
- ▸Context window: 1M tokens vs 1M — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
- ▸Recency: Claude Haiku 5.5 is the newer model by about 2 months (released October 7, 2026), usually meaning fresher training data and capabilities.
- ▸Ecosystem: this is a US-vs-China matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
| Spec | Claude Haiku 5.5 | Kimi K3 |
|---|---|---|
| Provider | Anthropic (US) | Moonshot AI (China) |
| Released | October 7, 2026 | July 27, 2026 |
| Context window | 1M tokens (~1,500 pages) | 1M (~1,573 pages) |
| Price (in/out) | $0.1/$0.5 per 1M tokens | $3/$15 per 1M tokens |
| Open weight? | No — API only | Yes — self-hostable |
| Modalities | text, image, code | text, image, video, code |
| SWE-Bench Verified | Not published | Not published |
| MRCR v2 @ 1M | Not published | Not published |
Who wins what
5x the context window of Haiku 4.5 (1M vs 200K tokens) and double the max output (128K vs 64K)
Claude Haiku 5.5
Anthropic's October 7, 2026 small-model refresh — a 1M-token context window (up from 200K) at roughly 75% lower average cost than Haiku 4.5, priced at $0.10/$0.50 per million tokens — and it runs cheaper at $0.1/$0.5 per 1M tokens.
First Haiku-class model with an adjustable 'effort' setting to trade off cost, latency, and intelligence
Claude Haiku 5.5
At $0.1/$0.5 per 1M tokens it undercuts Kimi K3 ($3/$15 per 1M tokens), and that gap compounds at volume.
Anthropic's cheapest small model yet — runs about 75% cheaper on average than Haiku 4.5
Claude Haiku 5.5
Anthropic's October 7, 2026 small-model refresh — a 1M-token context window (up from 200K) at roughly 75% lower average cost than Haiku 4.5, priced at $0.10/$0.50 per million tokens — and it is the newer of the two.
Largest open-weight model at release — 2.8T sparse MoE, self-hostable
Kimi K3
Open weights make this possible at all — Claude Haiku 5.5 is API-only, so it cannot leave the vendor's servers.
1M-token context with native vision (text, image and video)
Kimi K3
Claude Haiku 5.5 is comparatively weak here — pricing jumps roughly 5x beyond 100K-token prompts ($0.50/$2.50 per million vs the headline $0.10/$0.50)
Vendor reports 81.2 FrontierSWE and 88.3 Terminal-Bench 2.1 on its own harness
Kimi K3
Moonshot's 2.8-trillion-parameter open-weight model — the largest open AI at release, with a 1M context and strong self-reported coding scores — and its weights are open while Claude Haiku 5.5 is API-only.
Lowest cost at scale
Claude Haiku 5.5
At $0.1/$0.5 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Claude Haiku 5.5
At $0.1/$0.5 per 1M tokens it undercuts Kimi K3, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Kimi K3
Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ Kimi K3
Open weights let you run it on your own hardware; Claude Haiku 5.5 is API-only.
Anyone whose priority is 5x the context window of haiku 4.5 (1m vs 200k tokens) and double the max output (128k vs 64k)
→ Claude Haiku 5.5
It is specifically built for that.
Anyone whose priority is largest open-weight model at release — 2.8t sparse moe, self-hostable
→ Kimi K3
That is its strongest area.
An enterprise with regional data-residency rules
→ Claude Haiku 5.5 or Kimi K3
Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
Claude Haiku 5.5: where it fits
Anthropic's October 7, 2026 small-model refresh — a 1M-token context window (up from 200K) at roughly 75% lower average cost than Haiku 4.5, priced at $0.10/$0.50 per million tokens. Released October 7, 2026 by Anthropic, it is built for 5x the context window of Haiku 4.5 (1M vs 200K tokens) and double the max output (128K vs 64K), first Haiku-class model with an adjustable 'effort' setting to trade off cost, latency, and intelligence, anthropic's cheapest small model yet — runs about 75% cheaper on average than Haiku 4.5, and over-refuses benign requests only 0.17% of the time on the API, down from Haiku 4.5's 0.44%.
Its trade-offs are real: pricing jumps roughly 5x beyond 100K-token prompts ($0.50/$2.50 per million vs the headline $0.10/$0.50), extended thinking can no longer be fully disabled — only dialed between low, medium, and high effort, and as the smallest tier, trails both Sonnet 5.5 and Opus 5.5 on hard reasoning and open-ended work. At $0.1 in / $0.5 out per million tokens, it sits in the budget price band.
Kimi K3: where it fits
Moonshot's 2.8-trillion-parameter open-weight model — the largest open AI at release, with a 1M context and strong self-reported coding scores. Released July 27, 2026 by Moonshot AI, it is built for largest open-weight model at release — 2.8T sparse MoE, self-hostable, 1M-token context with native vision (text, image and video), vendor reports 81.2 FrontierSWE and 88.3 Terminal-Bench 2.1 on its own harness, and fresh-input pricing of $3/M (cached $0.30/M), flat across the full 1M context.
Its trade-offs: coding scores use Moonshot FrontierSWE, not standard SWE-Bench Verified, 2.8T params need serious hardware to self-host — weights are free, running is not, no independent benchmark reproduction yet at release, and image input but no audio or video. At $3 in / $15 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
The defining split here is open vs. closed. Kimi K3 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Claude Haiku 5.5 gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.
Want both Claude Haiku 5.5 and Kimi K3 without two subscriptions? LumiChats gives you these plus 40+ models under one ₹69/day pass (about $1/day) — draft with one, cross-check with the other.
See pricingFrequently asked questions
Is Claude Haiku 5.5 or Kimi K3 better for coding?
Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, Claude Haiku 5.5 leans toward 5x the context window of haiku 4.5 (1m vs 200k tokens) and double the max output (128k vs 64k) while Kimi K3 leans toward largest open-weight model at release — 2.8t sparse moe, self-hostable, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Claude Haiku 5.5 or Kimi K3?
Kimi K3 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Claude Haiku 5.5 is API-metered at $0.1/$0.5 per 1M tokens. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.
Which has the bigger context window?
Effectively neither — 1M tokens vs 1M is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Claude Haiku 5.5 and Kimi K3 together?
Yes — a multi-model platform like LumiChats gives you Claude Haiku 5.5, Kimi K3 and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.
Which is newer, Claude Haiku 5.5 or Kimi K3?
Claude Haiku 5.5 — released October 7, 2026, about 2 months after Kimi K3.
Related comparisons
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.