Claude Haiku 5.5 vs GLM 4.7
Anthropic · US | Z.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 GLM 4.7 for genuinely permissive open weights — an mit-licensed 358b mixture-of-experts with no commercial restrictions or strong agentic coding for the price — 73.8% on swe-bench verified undercut most closed frontier models at launch. Choose GLM 4.7 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 GLM 4.7 (Z.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. GLM 4.7 is an MIT-licensed 358B open mixture-of-experts with strong 73.8% SWE-Bench Verified coding — but two generations behind GLM 5.2. 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 6× cheaper on input ($0.1/$0.5 per 1M tokens vs $0.6/$2.2 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
- ▸Context window: Claude Haiku 5.5 holds 4.9× more — 1M tokens (~1,500 pages) vs 200K (~304 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
- ▸Recency: Claude Haiku 5.5 is the newer model by about 10 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 | GLM 4.7 |
|---|---|---|
| Provider | Anthropic (US) | Z.ai (China) |
| Released | October 7, 2026 | December 22, 2025 |
| Context window | 1M tokens (~1,500 pages) | 200K (~304 pages) |
| Price (in/out) | $0.1/$0.5 per 1M tokens | $0.6/$2.2 per 1M tokens |
| Open weight? | No — API only | Yes — self-hostable |
| Modalities | text, image, code | text, code |
| SWE-Bench Verified | Not published | 73.8% |
| 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
Its 1M tokens window holds about 4.9× more than GLM 4.7's 200K in a single prompt.
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 GLM 4.7 ($0.6/$2.2 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
GLM 4.7 is comparatively weak here — text-only with no vision, and self-hosting a 358B model is a serious hardware commitment
Genuinely permissive open weights — an MIT-licensed 358B mixture-of-experts with no commercial restrictions
GLM 4.7
Open weights make this possible at all — Claude Haiku 5.5 is API-only, so it cannot leave the vendor's servers.
Strong agentic coding for the price — 73.8% on SWE-Bench Verified undercut most closed frontier models at launch
GLM 4.7
An MIT-licensed 358B open mixture-of-experts with strong 73.8% SWE-Bench Verified coding — but two generations behind GLM 5.2 — and its weights are open while Claude Haiku 5.5 is API-only.
An unusually generous 128K maximum output, which suits bulk refactors and long generation
GLM 4.7
GLM 4.7 lists an unusually generous 128K maximum output, which suits bulk refactors and long generation among its strengths; Claude Haiku 5.5 does not.
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.
Largest single-prompt input
Claude Haiku 5.5
Its 1M tokens window is about 4.9× larger than GLM 4.7's 200K, fitting roughly 1,500 pages in one prompt.
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 GLM 4.7, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Claude Haiku 5.5
Larger 1M tokens window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ GLM 4.7
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 genuinely permissive open weights — an mit-licensed 358b mixture-of-experts with no commercial restrictions
→ GLM 4.7
That is its strongest area.
An enterprise with regional data-residency rules
→ Claude Haiku 5.5 or GLM 4.7
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.
GLM 4.7: where it fits
An MIT-licensed 358B open mixture-of-experts with strong 73.8% SWE-Bench Verified coding — but two generations behind GLM 5.2. Released December 22, 2025 by Z.ai, it is built for genuinely permissive open weights — an MIT-licensed 358B mixture-of-experts with no commercial restrictions, strong agentic coding for the price — 73.8% on SWE-Bench Verified undercut most closed frontier models at launch, an unusually generous 128K maximum output, which suits bulk refactors and long generation, and cheap long-running agent loops thanks to aggressive prompt caching.
Its trade-offs: two generations behind — GLM 5, 5.1 and 5.2 have all shipped since, and new builds should default to those, its Verified lead narrows sharply on harder evaluations like SWE-Bench Pro, and text-only with no vision, and self-hosting a 358B model is a serious hardware commitment. At $0.6 in / $2.2 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
The defining split here is open vs. closed. GLM 4.7 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 GLM 4.7 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 GLM 4.7 better for coding?
Public SWE-Bench figures are not available for Claude Haiku 5.5, 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 GLM 4.7 leans toward genuinely permissive open weights — an mit-licensed 358b mixture-of-experts with no commercial restrictions, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Claude Haiku 5.5 or GLM 4.7?
GLM 4.7 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?
Claude Haiku 5.5 — 1M tokens vs 200K, about 4.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Claude Haiku 5.5 and GLM 4.7 together?
Yes — a multi-model platform like LumiChats gives you Claude Haiku 5.5, GLM 4.7 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 GLM 4.7?
Claude Haiku 5.5 — released October 7, 2026, about 10 months after GLM 4.7.
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.