Model Flags - Andi AIRun

Model flags let you choose which AI model to use. You can select by tier (Opus, Sonnet, Haiku) or specify an exact model ID.

Cross-Runtime Model Mapping

The same tier flag selects each runtime’s equivalent model:

Tier	Flag	Claude Code	Codex CLI
High	`--opus` / `--high`	claude-opus-4-7	gpt-5.4
Mid	`--sonnet` / `--mid`	claude-sonnet-4-6	gpt-5.3-codex
Low	`--haiku` / `--low`	claude-haiku-4-5	gpt-5.4-mini

Tier flags work the same way regardless of runtime. --opus always gives you the highest-tier model for whichever runtime is active.

Tier Flags

High Tier (Opus)

--opus

flag

Highest-tier model - Most capable, best for complex reasoning

ai --opus task.md
ai --aws --opus
ai --ollama --opus      # Not applicable to Ollama

Equivalent: --highDefault model: claude-opus-4-7Use for:

Complex architectural decisions
Difficult refactoring
Security analysis
High-stakes code generation

--high

flag

Alias for --opus

ai --high task.md

Mid Tier (Sonnet)

--sonnet

flag

Mid-tier model - Balanced capability and speed

ai --sonnet task.md
ai --aws --sonnet

Equivalent: --midDefault model: claude-sonnet-4-6Use for:

Most coding tasks
General development
Documentation
Code review

--mid

flag

Alias for --sonnet

ai --mid task.md

Low Tier (Haiku)

--haiku

flag

Lowest-tier model - Fastest and most cost-effective

ai --haiku task.md
ai --aws --haiku
ai --ollama --haiku     # Not applicable to Ollama

Equivalent: --lowDefault model: claude-haiku-4-5Use for:

Quick tests
Simple tasks
Cost-sensitive workloads
High-volume automation

--low

flag

Alias for --haiku

ai --low task.md

Custom Model Selection

--model

flag

Specify exact model ID - Use any model supported by your provider

ai --model claude-opus-4-7
ai --aws --model global.anthropic.claude-opus-4-7
ai --ollama --model qwen3-coder
ai --vercel --model openai/gpt-5.2-codex
ai --codex --model gpt-5.4

Format depends on provider:

AWS Bedrock: global.anthropic.claude-opus-4-7
Vertex AI: claude-opus-4-7
Anthropic API: claude-opus-4-7
Ollama: Model name from ollama list
Vercel: provider/model-name (e.g., openai/gpt-4)

Precedence: --model overrides tier flags (--opus, --sonnet, --haiku)

Model Defaults Per Provider

Claude Subscription (Pro/Max)

ai --pro                 # Uses your subscription's latest model

Claude Pro/Max doesn’t support tier selection - it always uses the latest available model from your subscription.

API Providers (AWS, Vertex, Anthropic, Azure)

Tier	Default Model
Opus (`--opus`, `--high`)	`claude-opus-4-7`
Sonnet (`--sonnet`, `--mid`)	`claude-sonnet-4-6`
Haiku (`--haiku`, `--low`)	`claude-haiku-4-5`

Default tier: High (Opus)

ai --aws                 # Uses Opus
ai --aws --sonnet        # Uses Sonnet
ai --aws --haiku         # Uses Haiku

Local Providers (Ollama, LM Studio)

ai --ollama --model qwen3-coder          # Specify model name
ai --lmstudio --model mlx-qwen-32b       # Specify model name

Local providers don’t have default models - you must specify with --model or configure a default in ~/.ai-runner/secrets.sh.

Codex CLI

Tier	Default Model
High (`--opus`, `--high`)	`gpt-5.4`
Mid (`--sonnet`, `--mid`)	`gpt-5.3-codex`
Low (`--haiku`, `--low`)	`gpt-5.4-mini`

Default: gpt-5.4 (Codex native default). Tier flags override: --mid selects gpt-5.3-codex.

ai --codex                   # Uses gpt-5.4 (native default)
ai --codex --mid             # Uses gpt-5.3-codex
ai --codex --haiku           # Uses gpt-5.4-mini

Override in ~/.ai-runner/secrets.sh:

export CODEX_MODEL_HIGH="gpt-5.4"
export CODEX_MODEL_MID="gpt-5.3-codex"
export CODEX_MODEL_LOW="gpt-5.4-mini"

Vercel AI Gateway

ai --vercel --model openai/gpt-5.2-codex        # OpenAI
ai --vercel --model anthropic/claude-opus-4.7   # Anthropic
ai --vercel --model google/gemini-exp-2506      # Google

Vercel supports 100+ models. Use provider/model-name format. See Vercel AI Gateway docs for available models.

Configuration

View Default Models

ai-status    # Shows default model IDs for each tier

Override Model Defaults

Edit ~/.ai-runner/secrets.sh:

# Override AWS Sonnet model
export CLAUDE_MODEL_SONNET_AWS="global.anthropic.claude-sonnet-4-6"

# Override small/fast model (for background operations)
export CLAUDE_SMALL_FAST_MODEL_AWS="us.anthropic.claude-haiku-4-5-20251001-v1:0"

# Override Vertex Opus model
export CLAUDE_MODEL_OPUS_VERTEX="claude-opus-4-7"

See ~/.ai-runner/models.sh for all available override variables.

Dual Model Configuration

Claude Code uses two models:

Primary model (ANTHROPIC_MODEL) - Interactive work, selected by tier flags
Small/fast model (ANTHROPIC_SMALL_FAST_MODEL) - Background operations (defaults to Haiku)

When you run:

ai --aws --opus

Primary: Opus (claude-opus-4-7)
Background: Haiku (claude-haiku-4-5)

Both models show in ai-status output.

Examples

Tier Selection

# Most capable (Opus)
ai --aws --opus complex-refactor.md

# Balanced (Sonnet, default)
ai --aws task.md
ai --aws --sonnet task.md     # Explicit

# Fastest/cheapest (Haiku)
ai --aws --haiku quick-test.md

Custom Models

# Specific AWS Bedrock model
ai --aws --model us.anthropic.claude-opus-4-7

# Ollama local model
ai --ollama --model qwen3-coder

# Ollama cloud model (no GPU needed)
ai --ollama --model minimax-m2.5:cloud

# Vercel with OpenAI
ai --vercel --model openai/gpt-5.2-codex

# Vercel with xAI Grok
ai --vercel --model xai/grok-2

Shebang Scripts

#!/usr/bin/env -S ai --aws --opus
Complex task requiring the most capable model.

#!/usr/bin/env -S ai --ollama --model qwen3-coder
Local execution with specific model.

Resume with Different Model

# Start with Sonnet
ai --aws --sonnet

# Resume with Opus for complex reasoning
ai --aws --opus --resume

# Resume with Haiku for speed
ai --aws --haiku --resume

Cost Optimization

# Use Haiku for bulk operations
for file in *.md; do
  ai --aws --haiku --skip "$file" >> results.txt
done

# Use Opus only for critical review
ai --aws --opus --skip final-review.md

Model Recommendations

Task Type	Recommended Tier	Reason
Complex refactoring	Opus	Needs deep understanding
Architectural design	Opus	High-stakes decisions
Security analysis	Opus	Accuracy critical
General coding	Sonnet	Balanced performance
Documentation	Sonnet	Good quality/speed ratio
Code review	Sonnet	Sufficient capability
Quick tests	Haiku	Speed matters
Bulk automation	Haiku	Cost-effective
Simple tasks	Haiku	Overhead not needed

Troubleshooting

Model not found error

Model IDs are provider-specific. Check your provider’s available models:

# AWS Bedrock
aws bedrock list-foundation-models --region us-west-2

# Ollama
ollama list

# Vertex AI
gcloud ai models list --region=us-central1

See provider documentation for correct model ID format.

Wrong model being used

Check for overrides in ~/.ai-runner/secrets.sh:

grep CLAUDE_MODEL ~/.ai-runner/secrets.sh

Verify active model in session:

ai-status

Tier flags don't work with Ollama

Tier flags work differently with local and Codex providers. For Ollama/LM Studio, you may need --model to specify a local model name. For Codex, tiers map to GPT models automatically.

ai --ollama --model qwen3-coder

Provider Flags

Switch between cloud providers

Provider Model Lists

Available models per provider

Commands

Flags

​Cross-Runtime Model Mapping

​Tier Flags

​High Tier (Opus)

​Mid Tier (Sonnet)

​Low Tier (Haiku)

​Custom Model Selection

​Model Defaults Per Provider

​Claude Subscription (Pro/Max)

​API Providers (AWS, Vertex, Anthropic, Azure)

​Local Providers (Ollama, LM Studio)

​Codex CLI

​Vercel AI Gateway

​Configuration

​View Default Models

​Override Model Defaults

​Dual Model Configuration

​Examples

​Tier Selection

​Custom Models

​Shebang Scripts

​Resume with Different Model

​Cost Optimization

​Model Recommendations

​Troubleshooting

​Related Pages

Provider Flags

Provider Model Lists

Cross-Runtime Model Mapping

Tier Flags

High Tier (Opus)

Mid Tier (Sonnet)

Low Tier (Haiku)

Custom Model Selection

Model Defaults Per Provider

Claude Subscription (Pro/Max)

API Providers (AWS, Vertex, Anthropic, Azure)

Local Providers (Ollama, LM Studio)

Codex CLI

Vercel AI Gateway

Configuration

View Default Models

Override Model Defaults

Dual Model Configuration

Examples

Tier Selection

Custom Models

Shebang Scripts

Resume with Different Model

Cost Optimization

Model Recommendations

Troubleshooting

Related Pages