Current AI Models as of July 2026
July 2026 turned out to be eventful: GPT-5.6, Grok 4.5, and Muse Spark 1.1 launched within a single week, and Claude Fable 5 returned after a nearly three-week pause. Below are the current models and agents covered in this article:
- OpenAI: GPT-5.6 Sol, Terra, Luna; GPT-5.5; ChatGPT Work; ChatGPT Images 2.0; Codex
- Anthropic: Claude Fable 5, Opus 4.8, Sonnet 5; Claude Cowork
- Google: Gemini 3.1 Pro, Gemini 3.5 Flash; Gemini Spark; Veo 3.1
- xAI: Grok 4.5
- Meta: Muse Spark 1.1
- ByteDance: Seedream 5.0 Pro
- Alibaba: Qwen 3.7 Max (API); Qwen 3 235B-A22B, Qwen 3.5, Qwen 3.6 (open weights)
- Open-source: Llama 4 Scout and Maverick; DeepSeek V4, R1, V3; Mistral Large 3, Small 4; GLM-5, GLM-4.7; Gemma 3, Gemma 4 26B A4B; Phi-4; Kimi K2.6
The flagship model market no longer boils down to a single winner - each family has its own strength, and the choice depends on task, budget, and context requirements.
Market overview
By mid-2026, a stable three-pole structure had formed:
- OpenAI - GPT-5.6 (Sol, Terra, Luna) and the ChatGPT / Codex / ChatGPT Work ecosystem
- Anthropic - Claude Fable 5, Opus 4.8, Sonnet 5, and the Claude Cowork agent
- Google - Gemini 3.1 Pro, Gemini 3.5 Flash, and the Gemini Spark agent
Alongside them are specialized players: xAI (Grok 4.5), Meta (Muse Spark 1.1), ByteDance (Seedream 5.0 Pro for images), Alibaba (Qwen 3.7 Max). In parallel, the mature open-source segment closes the gap with closed flagships to within a few points on key benchmarks - Llama 4, Qwen 3.x, DeepSeek V4, Mistral Large 3, and GLM-5 are already production-ready with self-hosting. Competition has shifted from who is smarter to who is more efficient on a specific task at an acceptable price.
Below is the current state of the main model lines as of July 11, 2026.
OpenAI: GPT-5.6 family
On July 9, OpenAI opened GPT-5.6 to all users. The model became the default in ChatGPT after a limited preview accompanied by regulatory reviews.
Three tiers in one generation
| Model | Role | Context | Input / 1M | Output / 1M |
|---|---|---|---|---|
| Sol | Flagship: code, agents, complex tasks | 1.05M | $5.00 | $30.00 |
| Terra | Balance of price and quality | 1.05M | $2.50 | $15.00 |
| Luna | Fast and economical | 1.05M | $1.00 | $6.00 |
| GPT-5.5 | Previous flagship, fallback | 1M | $5.00 | $30.00 |
For input above 272K tokens, GPT-5.6 uses long-context pricing: input x2, output x1.5 (Sol: $10 / $45 per 1M).
Sol is positioned as OpenAI's best coding model: according to the Artificial Analysis Coding Agent Index, it outperforms Claude Fable 5 with lower token usage and cost. Terra and Luna cover mass scenarios - from everyday chat to background automation.
GPT-5.5 remains the fallback where proven stability is needed. Sol showed increased agentic behavior in some scenarios, so for production-critical tasks it makes sense to test both versions.
ChatGPT Work
Along with GPT-5.6, ChatGPT Work was announced - an agent for office tasks: documents, spreadsheets, presentations, simple web apps. It combines ChatGPT and Codex capabilities and competes with Claude Cowork. Integrations with Slack, Gmail, Google Drive, calendars, and CRM are supported.
Anthropic: Claude after the pause
On July 1, Anthropic brought back Claude Fable 5 - the Mythos-class flagship removed on June 12 due to US export restrictions. The model's return noticeably changed the landscape in coding and long agentic scenarios.
Key models in the lineup
| Model | Use case | Context | Input / 1M | Output / 1M |
|---|---|---|---|---|
| Claude Fable 5 | Coding, long agentic workflows | 1M | $10.00 | $50.00 |
| Claude Opus 4.8 | Daily work, enterprise | 1M | $5.00 | $25.00 |
| Claude Sonnet 5 | Text, instructions (intro through Aug 31) | 1M | $2.00 | $10.00 |
From September 1, 2026, Claude Sonnet 5: $3.00 input / $15.00 output per 1M.
Claude Cowork - an agent for collaborative work with files and apps, OpenAI's direct response to ChatGPT Work. For teams already using Claude Code, Cowork is a natural addition to the dev stack.
Google: Gemini 3.x
Google runs the lineup in two dimensions - reasoning and price-performance.
| Model | Use case | Context | Input / 1M | Output / 1M |
|---|---|---|---|---|
| Gemini 3.1 Pro | Complex reasoning, accuracy | 1M | $2.00 | $12.00 |
| Gemini 3.5 Flash | Price-performance, long context | 2M | $1.50 | $9.00 |
Above 200K tokens, Gemini 3.1 Pro uses elevated pricing: $4.00 input / $18.00 output per 1M.
Gemini's strength is long context and multimodality. For analyzing large document sets, codebases, and mixed data (text + images), this is often the deciding factor.
Gemini Spark - Google's agent, one of the two most visible agentic products of summer 2026 alongside Claude Cowork.
xAI, Meta, ByteDance, and Alibaba
| Model | Use case | Context | Input / 1M | Output / 1M |
|---|---|---|---|---|
| Grok 4.5 | Code, real-time X context | 1M | $2.00 | $6.00 |
| Meta Muse Spark 1.1 | Accessible mid-tier API | 256K | $1.25 | $4.25 |
| Qwen 3.7 Max | Mid-tier reasoning (API) | 1M | $2.50 | $7.50 |
| Seedream 5.0 Pro | Image generation | - | per image | per image |
Grok 4.5 is strong with Cursor and tasks that need up-to-date context from X and the web. Qwen 3.7 Max - closed weights via Alibaba Cloud; the open-source Qwen lineup is described below. Seedream 5.0 Pro is billed per image, not per token.
Open-source models
Open weights are a separate market layer that in 2026 is no longer a backup option for experiments. Several models match GPT-4-class on code and reasoning, and DeepSeek V4 and GLM-5.1 compete with closed flagships on SWE-Bench. Main reasons to choose open-source: self-hosting, data control, predictable cost at scale, and no vendor lock-in.
Open-source model prices below are from OpenRouter as of July 11, 2026 (hosted inference without deploying your own hardware). Self-hosting remains possible - then per-token billing does not apply.
Meta: Llama 4
| Model | Use case | Context | Input / 1M | Output / 1M |
|---|---|---|---|---|
| Llama 4 Scout | RAG, large archives | 10M | $0.10 | $0.30 |
| Llama 4 Maverick | General-purpose | 1M | $0.15 | $0.60 |
Prices - OpenRouter. With self-hosting, there is no per-token charge; cost is hardware and electricity only.
The Llama 4 Community license restricts products with over 700M MAU - for most B2B projects this is not an issue; large consumer platforms need a separate review.
Alibaba: Qwen (open weights)
Cloud Qwen 3.7 Max and the open-source lineup are different products. For self-hosting, these are relevant:
| Model | Use case | Context | Input / 1M | Output / 1M |
|---|---|---|---|---|
| Qwen 3 235B-A22B | Reasoning + coding | 131K | $0.46 | $1.82 |
| Qwen 3.5-397B-A17B | Multilingual, science | 256K | $0.39 | $2.45 |
| Qwen 3.6-35B-A3B | Single server, quantization | 262K | $0.14 | $1.00 |
Qwen is the most common choice when you need a balance of quality, Apache 2.0 license, and support in vLLM / Ollama / llama.cpp.
DeepSeek
| Model | Use case | Context | Input / 1M | Output / 1M |
|---|---|---|---|---|
| DeepSeek V4 Flash | Coding, agents, budget | 1M | $0.08 | $0.17 |
| DeepSeek V4 Pro | Complex reasoning | 1M | $0.44 | $0.87 |
| DeepSeek R1 | Math, deep reasoning | 164K | $0.70 | $2.50 |
| DeepSeek V3.2 | General-purpose fallback | 131K | $0.21 | $0.32 |
On OpenRouter, DeepSeek V4 Flash is cheaper than through the direct DeepSeek API. The direct API doubles rates during peak hours (9:00-12:00 and 14:00-18:00 CST) from mid-July 2026.
Mistral AI
| Model | Use case | Context | Input / 1M | Output / 1M |
|---|---|---|---|---|
| Mistral Large 3 | Multilingual, enterprise | 262K | $0.50 | $1.50 |
| Mistral Small 4 | Production chat + tools | 262K | $0.15 | $0.60 |
Mistral wins where a permissive license without MAU cap, European data residency, and a mature deployment ecosystem matter.
Zhipu AI: GLM
| Model | Use case | Context | Input / 1M | Output / 1M |
|---|---|---|---|---|
| GLM-5.1 | Agentic coding | 203K | $0.97 | $3.04 |
| GLM-4.7 | Coding workflows | 203K | $0.40 | $1.75 |
Google and Microsoft: compact models
| Model | Use case | Context | Input / 1M | Output / 1M |
|---|---|---|---|---|
| Gemma 3 27B | Single GPU | 131K | $0.08 | $0.16 |
| Gemma 4 26B A4B | Math + coding | 262K | $0.06 | $0.33 |
| Phi-4 | Edge, laptop | 16K | $0.07 | $0.14 |
Kimi K2.6
| Model | Use case | Context | Input / 1M | Output / 1M |
|---|---|---|---|---|
| Kimi K2.6 | Agentic coding | 262K | $0.66 | $3.41 |
Kimi K2.6 (Moonshot AI) - an open-weight model focused on agentic coding and long development sessions. Often mentioned alongside DeepSeek V4 and GLM-5 as top-tier for autonomous coding agents.
Open-source flagship comparison
| Model | Strength | Context | Input / 1M | Output / 1M | License |
|---|---|---|---|---|---|
| Qwen 3 235B-A22B | Reasoning + coding | 131K | $0.46 | $1.82 | Apache 2.0 |
| DeepSeek V4 Flash | Coding + agents | 1M | $0.08 | $0.17 | MIT |
| DeepSeek V4 Pro | Complex reasoning | 1M | $0.44 | $0.87 | MIT |
| DeepSeek R1 | Math + deep reasoning | 164K | $0.70 | $2.50 | MIT |
| Llama 4 Scout | Long context | 10M | $0.10 | $0.30 | Llama 4 Community |
| Mistral Large 3 | Multilingual + enterprise | 262K | $0.50 | $1.50 | Apache 2.0 |
| Mistral Small 4 | Production chat + tools | 262K | $0.15 | $0.60 | Apache 2.0 |
| GLM-5.1 | Agentic coding | 203K | $0.97 | $3.04 | MIT |
| Qwen 3.6-35B-A3B | Single-server deploy | 262K | $0.14 | $1.00 | Apache 2.0 |
| Gemma 3 27B | Single GPU | 131K | $0.08 | $0.16 | Gemma |
| Gemma 4 26B A4B | Math + coding | 262K | $0.06 | $0.33 | Apache 2.0 |
| Phi-4 | Edge / laptop | 16K | $0.07 | $0.14 | MIT |
| Kimi K2.6 | Agentic coding | 262K | $0.66 | $3.41 | Open weights |
All prices - OpenRouter, July 2026. With self-hosting, factor in GPU and electricity costs instead of per-token billing.
When to choose open-source
Open-source makes sense if:
- data must not leave your perimeter (on-premise, private cloud)
- you need predictable cost at scale with millions of requests per month
- fine-tuning for your domain without API restrictions matters
- your team already runs GPU infrastructure or uses vLLM / TGI
Closed APIs (GPT-5.6, Claude, Gemini) remain preferable when you need out-of-the-box agents (ChatGPT Work, Cowork, Spark), minimal time-to-market without DevOps, and access to the latest multimodal capabilities without deployment.
Multimodality: images and video
Text LLMs are only part of the ecosystem:
- ChatGPT Images 2.0 - image generation with readable text on the image
- Google Veo 3.1 - leader among video models after OpenAI shut down the Sora 2 consumer app
- Seedream 5.0 Pro - alternative for design and marketing materials
The choice depends on whether you want a unified stack (OpenAI / Google) or the best quality in a specific modality.
How to choose a model by task
There is no universal best AI. A practical scheme:
| Task | What to look at first |
|---|---|
| Daily chat and documents | GPT-5.6 Terra or Luna, Claude Opus 4.8 |
| Programming and agents | GPT-5.6 Sol, Claude Fable 5 |
| Long context (code, archives) | Gemini 3.5 Flash, Gemini 3.1 Pro |
| Text and editing | Claude Sonnet 5 |
| Budget and API automation | GPT-5.6 Luna, Grok 4.5, Qwen 3.7 Max |
| Self-hosting and on-premise | Qwen 3 235B-A22B, DeepSeek V4, Mistral Small 4, Llama 4 Scout |
| Coding on your own hardware | DeepSeek V4, GLM-5.1, Qwen 3.6-35B-A3B |
| Single GPU / edge | Gemma 3 27B, Phi-4, Qwen 3.6-35B-A3B (OpenRouter) |
| Long context (local) | Llama 4 Scout, Qwen 3.6 |
| Real-time news and X | Grok 4.5 |
| Office automation | ChatGPT Work, Claude Cowork, Gemini Spark |
| Images / video | ChatGPT Images 2.0, Veo 3.1, Seedream 5.0 Pro |
For production, keep an abstraction over providers: route by task type, fallback to GPT-5.5 or Opus 4.8 on failures, and monitor token costs separately.
What changed in the last month
- GPT-5.6 reached GA - OpenAI regained leadership in coding benchmarks and lowered flagship cost vs competitors
- Claude Fable 5 is back - Anthropic restored its position in SWE and agentic scenarios
- Agents went mainstream - ChatGPT Work, Claude Cowork, and Gemini Spark turn LLMs from chat into work tools
- Price war intensified - Luna, Grok 4.5, and Muse Spark 1.1 pressure the mid-tier and split the API integration market
- Regulation became a factor - the Fable 5 pause showed top-model access can change quickly
- Open-source caught the closed frontier - DeepSeek V4, GLM-5.1, and Qwen 3.6 reached SWE-Bench levels comparable to GPT-5.5 and Opus 4.8
Summary
In July 2026, the AI market is mature and fragmented. GPT-5.6 Sol and Claude Fable 5 share first place in coding among closed APIs; Gemini 3.5 Flash leads in long context and price-performance; Claude Sonnet 5 leads in text work. In open-source, Qwen 3 235B-A22B, DeepSeek V4, and Llama 4 Scout lead - each with a narrow specialization. Agent products (ChatGPT Work, Cowork, Spark) are the next layer on top of models.
For business, the optimal strategy is not to lock into one vendor: test 2-3 models on real tasks, calculate cost per task, not just price per million tokens, and plan fallback - to the previous API generation (GPT-5.5, Opus 4.8) or self-hosted open-source (DeepSeek V4, Mistral Small 4) when data and budget require it.
Frequently asked questions
Which model is best for programming in July 2026?
Among closed APIs, GPT-5.6 Sol and Claude Fable 5 lead - both strong in coding and agentic scenarios. Sol wins on output token cost; Fable 5 on SWE-Bench Pro (~80.3%). For budget API - Grok 4.5 ($2 / $6) or GPT-5.6 Luna ($1 / $6). In open-source - DeepSeek V4 Flash on OpenRouter ($0.08 / $0.17) and GLM-5.1.
Open-source or closed API - which to choose?
Open-source (via OpenRouter or self-hosting) - if data control, predictable cost at scale, and no vendor lock-in matter. Closed API (GPT-5.6, Claude, Gemini) - if you need out-of-the-box agents (ChatGPT Work, Cowork, Spark), multimodality without DevOps, and minimal time-to-market. For many teams, a hybrid works best: closed API for product features, open-source for background automation.
How do GPT-5.6 Sol, Terra, and Luna differ?
All three are one generation with 1.05M token context but different capability levels and price. Sol ($5 / $30) - flagship for complex code and agents. Terra ($2.50 / $15) - balance for daily work. Luna ($1 / $6) - mass tasks: classification, data extraction, routine chat. ChatGPT Free and Go default to Terra.
Why was Claude Fable 5 unavailable and is it back?
On June 12, 2026, Anthropic removed Fable 5 due to US export restrictions on frontier models. On June 30 the restriction was lifted; on July 1 the model returned to the API and competing services at the same price ($10 / $50). The pause showed top-model access can change for regulatory reasons - keep a fallback (Opus 4.8, GPT-5.6 Sol).
How to save on API without losing quality?
Three practical approaches: task routing - Luna or DeepSeek V4 Flash for simple requests, Sol or Fable 5 only for complex ones; OpenRouter for open-source models - often cheaper than direct API (e.g. DeepSeek V4 Flash $0.08 vs $0.14); prompt caching and batch API - up to 50-90% savings on repeated context. Calculate cost per task, not just price per million tokens - a cheap model with long output can cost more overall.