State of LLMs: The Complete Guide (2025–2026)
Last updated: February 17, 2026
All data verified from official sources (OpenAI, Anthropic, Google, xAI, DeepSeek, Alibaba, Meta, etc.). Prices in USD per 1M tokens unless noted. Leaderboards: SWE-Bench Verified, ARC-AGI-2, Terminal-Bench, LMSYS Arena.
The frontier has never been closer to commodity. Chinese models have redrawn the price/performance line. Opus 4.6 and GPT-5.3-Codex remain kings for high-stakes work. And Grok 5 is weeks away.
Index
1. Frontier Model Overview (February 2026)
| Model (Vendor) | Release Date | Parameters & Architecture | Max Context | Hallmark Strengths | Best For | Cost Tier |
|---|
| Claude Opus 4.6 (Anthropic) | Feb 5, 2026 | ~400B+ MoE | 1M (beta) / 200K std | 82%+ SWE-Bench, parallel sub-agents, 500+ zero-days discovered | High-stakes coding & security | Premium |
| GPT-5.3-Codex (OpenAI) | Feb 5, 2026 | ~1.8T+ adaptive MoE + recursive self-debug | 400K (128K output) | Best agentic coding, terminal control, enterprise repos | Professional coding & agents | High |
| Gemini 3 Pro + Deep Think (Google) | Nov 2025 (Deep Think Feb 12, 2026) | Dense multimodal | 1M+ | PhD-level science/engineering, ARC-AGI 84.6% | Research, complex analytics | Low-Mid |
| Grok 4.1 Fast (xAI) | Nov 19, 2025 | ~500B hybrid MoE | 2M | Real-time X data, emotional intelligence, lowest price for frontier | Real-time analysis, creative agents | Low-Mid |
| Qwen3.5 Plus (Alibaba) | Feb 15, 2026 | 397B MoE (A17B active) | 1M | Insane price/performance, multilingual | High-volume production & cost-sensitive | Ultra Low |
| Llama 4 Maverick (Meta) | Apr 5, 2025 | 400B MoE (17B active) | 1M | Fully open weights, native multimodal | Customisation & on-prem | Free / Low |
| Claude Sonnet 4.6 / Haiku 4.6 (Anthropic) | Early Feb 2026 | Compact MoE | 200K / 128K | Speed + 80% of Opus performance | Daily coding & agents | Mid |
| GLM-5 (Zhipu AI) | Late 2025 | — | 200K+ | 77.8% SWE-Bench, strong agentic workflows | Open-source agentic leader | Low |
| Kimi K2.5 (Moonshot AI) | Late 2025 | — | 262K | Multimodal + agentic planning | Task execution & planning | Low |
| MiniMax M2.5 (MiniMax) | Late 2025 | — | 205K | Code-native language frameworks | Code generation & debugging | Ultra Low |
2. Quick API Pricing Snapshot (Feb 2026)
| Model | Context | Input ($/M) | Output ($/M) | Notes |
|---|
| MiniMax M2.5 | 205K | $0.15 | $0.60 | Ultra-budget |
| Qwen3.5 397B A17B | 262K | $0.15 | $1.00 | Flagship at commodity pricing |
| Qwen3.5 Plus (Feb 15) | 1M | $0.40 | $2.40 | Best price/performance ever |
| Moonshot Kimi K2.5 | 262K | $0.23 | $3.00 | Multimodal + agentic |
| Zhipu GLM-5 | 205K | $0.30 | $2.55 | Open-source agentic |
| Claude Sonnet 4.6 | 200K–1M | $3.00 | $15.00 | Daily driver |
| GPT-5.3-Codex | 400K | $1.75 | $14.00 | Structured outputs |
| Grok 4.1 | 2M | $3.00 | $15.00 | Real-time X data |
| Gemini 3 Pro (≤200K) | 1M+ | $2.00 | $12.00 | Multimodal native |
| Claude Opus 4.6 | 1M (beta) | $5.00 | $25.00 | Coding king |
3. Key Innovations (February 2026)
| Innovation | Lead Model(s) | Key Numbers / Facts |
|---|
| Parallel Sub-Agent Planning | Claude Opus 4.6 | Breaks tasks into 10+ independent sub-agents working simultaneously |
| Recursive Self-Debug | GPT-5.3-Codex | Fixes its own code in live terminals; iterative error correction |
| 2M Real-Time Context | Grok 4.1 Fast | Native X feed integration + largest production context window |
| Deep Think Science Mode | Gemini 3 Pro (Feb 12 upgrade) | 84.6% ARC-AGI-2, IMO-Gold++ level mathematical reasoning |
| 1M Context at $0.40/M | Qwen3.5 Plus | Best price/performance ratio in LLM history |
| Open MoE Distillation | Llama 4 Maverick | 400B model distilled from unreleased Behemoth; fully open weights |
| Zero-Day Discovery at Scale | Claude Opus 4.6 | 500+ zero-day vulnerabilities found in a single security audit run |
4. Context Window Tiers (Feb 2026)
| Tier | Token Range | Top Models |
|---|
| Massive | 1M – 2M | Grok 4.1 (2M), Qwen3.5 Plus (1M), Claude Opus 4.6 beta (1M), Gemini 3 Pro (1M+) |
| Large | 400K | GPT-5.3-Codex |
| Standard | 128K – 262K | Kimi K2.5 (262K), Qwen3.5 (262K), GLM-5 (205K), MiniMax M2.5 (205K), Claude Sonnet/Haiku 4.6 (200K), most others |
5. Best-Pick Matrix (Feb 2026)
| Use Case | Top Model | Why It Wins |
|---|
| Professional Coding / Agents | Claude Opus 4.6 / GPT-5.3-Codex | 82%+ SWE-Bench; terminal control + security + repo-scale |
| Cost-Efficient Production | Qwen3.5 Plus / Grok 4.1 Fast | 1M context under $3/M total blended cost |
| Research & Science | Gemini 3 Pro Deep Think | Highest raw reasoning on messy real-world data; 84.6% ARC-AGI-2 |
| Real-Time + Creative | Grok 4.1 Fast | 2M context + live X data + personality |
| On-Prem / Customisation | Llama 4 Maverick | Full open weights + multimodal + 1M context |
| Security & Compliance | Claude Opus 4.6 | 500+ zero-day discoveries in one run; enterprise audit-ready |
| Daily Driver (Speed + Quality) | Claude Sonnet 4.6 | 80% of Opus performance at 60% of the cost |
| Multilingual / Global | Qwen3.5 Plus | Best multilingual coding and text across CJK + Latin languages |
| Open-Source Agentic | GLM-5 (Zhipu AI) | 77.8% SWE-Bench; strong tool use; open weights |
| Budget Frontier Coding | DeepSeek V4 / R1 | 75–77% SWE-Bench at 0.03−0.55/M input |
6. Global LLM Directory (By Country of Origin)
Beyond the frontier models above, the broader LLM ecosystem spans many countries and specialisations.
Canada
| Model | Company | Best For |
|---|
| Cohere | Cohere | Enterprise NLU; excels in summarisation, search, RAG, and custom fine-tuning |
China
| Model | Company | Best For |
|---|
| Qwen / Qwen3 / Qwen3.5 | Alibaba | Multilingual + coding; 235B–397B parameter flagships; specific variants for coding (Qwen3-Coder) |
| DeepSeek | DeepSeek | High-performance LLMs; DeepSeek-Coder for specialised coding; DeepSeek-R1 for reasoning; ultra-low pricing |
| GLM / GLM-5 | Zhipu AI | Models optimised for tool use and agentic workflows; open-source |
| Kimi / K2.5 | Moonshot AI | Multimodal LLM with agentic capabilities for planning and executing tasks |
| MiniMax M2.5 | MiniMax | Code-native language frameworks for code generation and debugging |
| Baichuan | Baichuan | Open-source enterprise model with multi-modal capabilities (text, images, video, audio) |
| Ernie Bot | Baidu | General-purpose LLM; one of the first approved for public use in China |
| Hunyuan | Tencent | Generative model suite for enterprise and cloud applications |
| Yi | 01.AI | Exceptional bilingual (Chinese–English) performance |
| RWKV | RWKV Foundation | Efficient recurrent architecture for long-context tasks; open-source with strong bilingual and coding efficiency |
| ByteDance Models | ByteDance | Expanding from consumer apps to enterprise tools; multilingual focus |
France
| Model | Company | Best For |
|---|
| Mistral | Mistral AI | Lightweight, efficient models for deployment; strong in coding, multilingual tasks, and open-source customisation |
United States
| Model | Company | Best For |
|---|
| Claude (3 → 4.6 family) | Anthropic | Advanced reasoning, ethical AI, long-context tasks; 82%+ SWE-Bench (Opus 4.6); strong in coding and agentic workflows |
| GPT (3.5 → 5.3 family) | OpenAI | General-purpose + coding; creative writing, reasoning, chat; multimodal (text, image, voice); o-series for deep reasoning |
| Gemini (1.5 → 3 family) | Google | Multimodal processing (text, images, video, audio); search-integrated; Deep Think for science-level reasoning |
| Grok (2 → 4.1) | xAI | Real-time knowledge from X; largest context (2M); creative + conversational; competitive pricing |
| Llama (1 → 4 family) | Meta | Foundational open-source models; from 1B to 400B+ parameters; fully open weights; multimodal (Llama 4) |
| PaLM | Google | Predecessor to Gemini; excels in reasoning benchmarks and large-scale data processing (legacy) |
7. Model Evolution at a Glance
OpenAI (GPT Family)
| Generation | Key Models | Context | Standout Features |
|---|
| GPT-3.5 | GPT-3.5 Turbo | 16K | Fast, cheap, legacy workhorse |
| GPT-4 | GPT-4, GPT-4 Turbo, GPT-4o, GPT-4.1 | 8K–1M | Multimodal; GPT-4o mini for budget |
| GPT-4.5 | GPT-4.5 Preview | 128K | Bridge generation |
| GPT-5 | GPT-5, GPT-5 mini, GPT-5 Nano, GPT-5.3-Codex | 400K | Recursive self-debug; structured outputs; nano tier at $0.05/M in |
| o-Series | o1, o1-mini, o3, o3-mini, o3-pro, o4-mini | 200K | Chain-of-thought reasoning; science & math optimised |
Anthropic (Claude Family)
| Generation | Key Models | Context | Standout Features |
|---|
| Claude 3 | Opus, Sonnet, Haiku | 200K | First generation with tiered model lineup |
| Claude 3.5/3.7 | Sonnet 3.5/3.7 | 200K | Extended thinking; price reductions |
| Claude 4 | Opus 4, Sonnet 4 | 200K–1M | Enhanced coding/reasoning; 1M for tiered orgs |
| Claude 4.6 | Opus 4.6, Sonnet 4.6, Haiku 4.6 | 1M (beta) / 200K | 82%+ SWE-Bench; parallel sub-agents; Claude Code in $20 Pro |
Google (Gemini Family)
| Generation | Key Models | Context | Standout Features |
|---|
| PaLM | PaLM 2 | 32K | Predecessor; reasoning benchmarks |
| Gemini 1.5 | Pro, Flash | 1M | Long-context pioneer |
| Gemini 2/2.5 | Pro, Flash, Flash-Lite | 1M+ | Multimodal (text/img/video/audio); Live API |
| Gemini 3 | Pro, Flash, Flash-Lite | 1M+ | Deep Think (Feb 12, 2026): 84.6% ARC-AGI-2; IMO-Gold++ |
Meta (Llama Family)
| Generation | Key Models | Context | Standout Features |
|---|
| Llama 1 | 7B–65B | 2K | Foundational open-source release |
| Llama 2 | 7B–70B | 4K | Fine-tuning friendly; bilingual |
| Llama 3/3.1/3.3 | 8B–405B | 8K–128K | Multilingual (8 languages); frontier-level open-source |
| Llama 4 | Scout, Maverick | 1M | 400B MoE (17B active); fully open weights; distilled from unreleased Behemoth |
xAI (Grok Family)
| Generation | Key Models | Context | Standout Features |
|---|
| Grok 2 | grok-2, grok-2-vision | 131K | Vision capabilities |
| Grok 3 | grok-3, grok-3-mini, grok-3-fast | 131K | Live Search ($25/1K sources) |
| Grok 4/4.1 | Grok 4, Grok 4.1 Fast | 2M | Largest context window; real-time X data; 3/15 per M |
Alibaba (Qwen Family)
| Generation | Key Models | Context | Standout Features |
|---|
| Qwen 2/2.5 | Turbo, Plus, Max, VL-Max, 72B/7B | 32K–1M | Tiered pricing; vision variants |
| Qwen 3 | 235B Thinking, Coder-Plus, Max-Preview | 262K | 1T+ parameter flagship (Max-Preview) |
| Qwen 3.5 | Qwen3.5 Plus, Qwen3.5 397B | 1M | Best price/performance ever: 0.40/2.40 per M at 1M context |
8. Benchmark Leaderboard Snapshot (Feb 17, 2026)
| Benchmark | #1 Model | Score | #2 Model | Notes |
|---|
| SWE-Bench Verified | Claude Opus 4.6 | ~81–82% | GPT-5.3-Codex (~80%) | Gold standard for real-world coding |
| ARC-AGI-2 | Gemini 3 Pro Deep Think | 84.6% | Claude Opus 4.6 (68.8%) | General reasoning / intelligence |
| Terminal-Bench 2.0 | Claude Opus 4.6 | 65.4% | GPT-5.3-Codex (~62%) | Agentic terminal tasks |
| Aider Leaderboard | Claude 4.6 family | Top | Qwen3.5 close behind | CLI-based code editing |
| LMSYS Arena (Coding) | Claude 4.6 Sonnet/Opus | Top blind votes | GPT-5.3 close | Human preference voting |
| LMSYS Arena (General) | GPT-5.3 / Claude 4.6 | Neck and neck | Gemini 3 Pro | Broad task preference |
9. What's Coming Next (Q1–Q3 2026)
| Model | Expected | Notes |
|---|
| Grok 5 | March 2026 | Trained on Colossus-2 supercluster; AGI-level claims from xAI. Most anticipated Q1 2026 release. |
| Llama 4 Behemoth | Q2 2026 | Still training; expected to beat GPT-5.3 on key benchmarks. Unreleased 2T+ model. |
| Claude 5 family | Mid-2026 | Full refresh of the Claude lineup |
| GPT-6 / o5 | H2 2026 (speculative) | No official confirmation; expected based on cadence |
| Gemini 4 | H2 2026 (speculative) | Likely deeper multimodal + agent integration |
10. Key Trends Shaping the LLM Landscape
-
Chinese Models Redraw Price/Performance — Qwen3.5 Plus (0.40/2.40), MiniMax M2.5 (0.15/0.60), and Kimi K2.5 (0.23/3.00) deliver frontier-adjacent quality at 90–95% lower cost than Western flagships.
-
1M+ Context is the New Normal — Grok 4.1 (2M), Qwen3.5 Plus (1M), Claude Opus 4.6 beta (1M), Gemini 3 Pro (1M+). "Doesn't fit in context" is no longer an excuse.
-
Open vs Closed Gap Shrunk Dramatically — Qwen3.5, GLM-5, Llama 4 Maverick are now within 3–5% of frontier on coding and reasoning benchmarks.
-
Agentic Architecture is Standard — Parallel sub-agents (Claude), recursive self-debug (GPT-5.3), and multi-step tool use are expected features, not innovations.
-
Mixture-of-Experts (MoE) Dominance — Nearly every new frontier model uses MoE. Qwen3.5 Plus activates only 17B of 397B parameters per forward pass, enabling massive models at tiny inference cost.
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Multimodality is Table Stakes — Text, image, video, audio, and code are all native inputs/outputs for 2026 frontier models. Vision-language models (VLMs) are no longer separate product lines.
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Reasoning Models as a Category — OpenAI's o-series (o3, o4-mini), Google's Deep Think, and extended thinking modes across vendors have established "slow thinking" as a distinct product tier for hard problems.
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February 2026 Release Wave — Claude Opus 4.6 (Feb 5), GPT-5.3-Codex (Feb 5), Gemini 3 Deep Think (Feb 12), and Qwen3.5 Plus (Feb 15) all landed in a single month, completely resetting the competitive landscape.
11. Data Jurisdiction & Compliance Notes
| Hosting Region | Providers | Considerations |
|---|
| US / EU | OpenAI, Anthropic, Google, xAI, Meta (via Groq/Deepinfra), Cohere, Mistral | GDPR/HIPAA-eligible; safe for sensitive/client data |
| China (PRC) | DeepSeek, Alibaba (Qwen), Zhipu AI (GLM), MiniMax, Moonshot (Kimi), Baidu, Tencent, ByteDance, 01.AI, RWKV, Baichuan | Data stored under PRC jurisdiction. Use only for non-sensitive work. Never send client code or proprietary data. |
| Self-Hosted | Llama 4 (Meta), GLM-5 (Zhipu), Mistral, Qwen (open-weight variants), RWKV | Full data control; nothing leaves your infrastructure |
Tip for Indian developers: Use US/EU-hosted providers (Groq, Google, OpenAI, Anthropic) for client work. China-hosted models are fine for experiments and non-sensitive prototyping.
12. Bottom Line — February 2026
- Chinese models (Qwen3.5 Plus, MiniMax, Kimi) have completely redrawn the price/performance frontier.
- Claude Opus 4.6 and GPT-5.3-Codex remain the kings of high-stakes professional work.
- Grok 4.1 Fast offers the best value + context combination right now (2M context, competitive pricing).
- Gemini 3 Pro Deep Think leads on pure reasoning and science (84.6% ARC-AGI-2).
- Llama 4 Maverick is the open-source champion — fully open weights, 1M context, multimodal.
- Grok 5 is the most anticipated release of Q1 2026.
The gap between "frontier" and "good enough for 99% of tasks" has never been smaller — and never cheaper.
Start building. The models are better and cheaper than ever. 🚀
