Claude Haiku 5.5 vs Mistral Large 4
Anthropic · US | Mistral AI · France · 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 Mistral Large 4 for mistral's largest model to date — 1.05t total parameters, 49b active per token (granular moe), plus a 1.6b-parameter vision encoder or trained from scratch on 3,800 nvidia grace blackwell gpus in mistral's own european data centers, across 160+ languages. On a tight budget at scale, Claude Haiku 5.5 is the value pick.
Claude Haiku 5.5 (Anthropic, US) and Mistral Large 4 (Mistral AI, France) 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. Mistral Large 4 is mistral's October 6, 2026 public preview of 'Le Chonk' — a 1.05T-parameter, natively multimodal MoE model with open weights planned by month's end. Their biggest split is price, and the breakdown below shows exactly how that plays out for your workload.
Key differences at a glance
- ▸Price: Claude Haiku 5.5 is about 6.8× cheaper on input ($0.1/$0.5 per 1M tokens vs $0.68/$2.09 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
- ▸Context window: both advertise 1M tokens (~1,500 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
- ▸Ecosystem: this is a US-vs-France matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
| Spec | Claude Haiku 5.5 | Mistral Large 4 |
|---|---|---|
| Provider | Anthropic (US) | Mistral AI (France) |
| Released | October 7, 2026 | October 6, 2026 |
| Context window | 1M tokens (~1,500 pages) | 1M tokens (~1,500 pages) |
| Price (in/out) | $0.1/$0.5 per 1M tokens | $0.68/$2.09 per 1M tokens |
| Open weight? | No — API only | No — API only |
| Modalities | text, image, code | text, image, 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 Mistral Large 4 ($0.68/$2.09 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
Mistral Large 4 is comparatively weak here — launch pricing ($0.68/$2.09 per million) is a preview discount — Mistral's own model page lists a $1.36/$4.18 list price once the promotion ends
Mistral's largest model to date — 1.05T total parameters, 49B active per token (granular MoE), plus a 1.6B-parameter vision encoder
Mistral Large 4
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)
Trained from scratch on 3,800 Nvidia Grace Blackwell GPUs in Mistral's own European data centers, across 160+ languages
Mistral Large 4
Mistral Large 4 lists trained from scratch on 3,800 Nvidia Grace Blackwell GPUs in Mistral's own European data centers, across 160+ languages among its strengths; Claude Haiku 5.5 does not.
Hybrid instruct/reasoning design — answers quickly by default or switches into step-by-step reasoning
Mistral Large 4
Claude Haiku 5.5 is comparatively weak here — as the smallest tier, trails both Sonnet 5.5 and Opus 5.5 on hard reasoning and open-ended work
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 Mistral Large 4, and on millions of tokens that margin decides the monthly bill.
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 mistral's largest model to date — 1.05t total parameters, 49b active per token (granular moe), plus a 1.6b-parameter vision encoder
→ Mistral Large 4
That is its strongest area.
An enterprise with regional data-residency rules
→ Claude Haiku 5.5 or Mistral Large 4
Origin (US vs France) 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.
Mistral Large 4: where it fits
Mistral's October 6, 2026 public preview of 'Le Chonk' — a 1.05T-parameter, natively multimodal MoE model with open weights planned by month's end. Released October 6, 2026 by Mistral AI, it is built for mistral's largest model to date — 1.05T total parameters, 49B active per token (granular MoE), plus a 1.6B-parameter vision encoder, trained from scratch on 3,800 Nvidia Grace Blackwell GPUs in Mistral's own European data centers, across 160+ languages, hybrid instruct/reasoning design — answers quickly by default or switches into step-by-step reasoning, and open weights planned by end of October 2026, which would make it among the largest open-weight models available.
Its trade-offs: still a public preview, not a finished release — Mistral says training is ongoing with 'no signs of saturation', weights not yet shipped as of mid-October 2026 — API-only for now despite the open-weight framing, launch pricing ($0.68/$2.09 per million) is a preview discount — Mistral's own model page lists a $1.36/$4.18 list price once the promotion ends, and scores 61.7% on DeepSWE v1.1, trailing DeepSeek V4.1 Flash (74.2%) and Kimi K3 (68.0%) on that coding benchmark. At $0.68 in / $2.09 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
This is less "which is smarter" and more "which ecosystem fits." Claude Haiku 5.5 (US) and Mistral Large 4 (France) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Claude Haiku 5.5 is the cheaper option, which matters at volume. The pragmatic move is to run one real task through both and judge the outputs against your own constraints — including where your data is allowed to be processed.
Want both Claude Haiku 5.5 and Mistral Large 4 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 Mistral Large 4 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 Mistral Large 4 leans toward mistral's largest model to date — 1.05t total parameters, 49b active per token (granular moe), plus a 1.6b-parameter vision encoder, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Claude Haiku 5.5 or Mistral Large 4?
Claude Haiku 5.5 is cheaper — $0.1/$0.5 per 1M tokens vs $0.68/$2.09 per 1M tokens, roughly 6.8× apart on input.
Which has the bigger context window?
Both advertise 1M tokens (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Claude Haiku 5.5 and Mistral Large 4 together?
Yes — a multi-model platform like LumiChats gives you Claude Haiku 5.5, Mistral Large 4 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 Mistral Large 4?
Claude Haiku 5.5 — released October 7, 2026, about 1 days after Mistral Large 4.
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.