Command A+ vs GPT-5 Codex

    Comparison

    As of August 20, 2026, GPT-5 Codex is 10% cheaper per million tokens than Command A+. Command A+ is $2.50 / $10.00 per million input/output tokens versus GPT-5 Codex at $1.25 / $10.00. Sources: https://anotherwrapper.com/tools/llm-pricing and https://developers.openai.com/api/docs/pricing

    Sources: AnotherWrapper LLM pricing (https://anotherwrapper.com/tools/llm-pricing); OpenAI API pricing (https://developers.openai.com/api/docs/pricing)

    Command A+

    Cohere

    $12.50blended / 1M

    Input

    $2.50

    Output

    $10.00

    ctx|Open Source
    10%
    cheaper
    Better value

    GPT-5 Codex

    OpenAI

    $11.25blended / 1M

    Input

    $1.25

    Output

    $10.00

    400K ctx|Proprietary
    Save $1.25 per million tokens by choosing GPT-5 Codex over Command A+.

    Command A+ vs GPT-5 Codex comparison

    Token pricing, specs, and benchmarks side by side

    Metric
    Command A+
    GPT-5 Codex
    Provider
    Provider
    Cohere
    OpenAI
    License
    Open Source
    Proprietary
    Release Date
    2026-05-20
    2025-09-15
    Pricing (per 1M tokens)
    Input Price+100%
    $2.50
    $1.25
    Output Price0%
    $10.00
    $10.00
    Blended (1M + 1M)
    $12.50
    $11.25
    Model Details
    Context Window
    N/A
    400K
    Max Output Tokens
    N/A
    N/A
    Knowledge Cutoff
    N/A
    2024-09-30
    Throughput
    N/A
    N/A

    Verdict

    Command A+ vs GPT-5 Codex: the bottom line

    Both models are closely matched on benchmarks. GPT-5 Codex has the pricing advantage, making it the better value unless Command A+'s specific capabilities are critical to your workflow.

    Command A+ vs GPT-5 Codex FAQ

    Which is cheaper, Command A+ or GPT-5 Codex?

    As of August 20, 2026, GPT-5 Codex is 10% cheaper on blended LLM API pricing. GPT-5 Codex costs $1.25 per million input tokens and $10.00 per million output tokens ($11.25 blended 1M-in + 1M-out). Command A+ costs $2.50 / $10.00 per million tokens ($12.50 blended). Sources: https://anotherwrapper.com/tools/llm-pricing and https://developers.openai.com/api/docs/pricing. The cheapest LLM for your app still depends on how many output tokens you generate.

    How much does Command A+ vs GPT-5 Codex cost per million tokens?

    Command A+ Cohere API pricing is $2.50 input and $10.00 output per million tokens via Cohere. GPT-5 Codex OpenAI API pricing is $1.25 input and $10.00 output per million tokens via OpenAI. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.

    Which is better for coding, Command A+ or GPT-5 Codex?

    GPT-5 Codex has a published SWE-bench Verified score of 74.5%. Command A+ does not have that eval on this page yet.

    What is the context window for Command A+ vs GPT-5 Codex?

    Command A+ supports a token context window, while GPT-5 Codex supports 400K tokens. GPT-5 Codex offers a larger context window. Filling a larger window bills more input tokens, so the cheaper-per-million model can still cost more on long documents.

    Which model performs better on benchmarks, Command A+ or GPT-5 Codex?

    Shared benchmark scores for Command A+ and GPT-5 Codex are still limited. Check the comparison table for the evals each model has published. Check the comparison table for GPQA Diamond, SWE-bench, MMLU, HLE, and the other evals we track. Token price and benchmark score together are the usual LLM comparison, not either number alone.

    Is Command A+ or GPT-5 Codex better for production use?

    Both Command A+ and GPT-5 Codex are production API models. For cost-sensitive production traffic, GPT-5 Codex has better economics on the blended 1M-in + 1M-out scale. For maximum capability, weight the benchmark table for your domain. Many production stacks route cheap models for drafts and a frontier model for the hard turn, which is usually cheaper than sending everything to the expensive API.

    Can I switch between Command A+ and GPT-5 Codex in my app?

    Yes. Call Command A+ through Cohere and GPT-5 Codex through OpenAI with separate API keys, or through a gateway that already wraps both. Keep prompts in tokens, not characters, when you estimate the invoice. AnotherWrapper templates can swap providers without rewriting auth and billing.

    How accurate is this Command A+ vs GPT-5 Codex pricing data?

    List rates are the latest published Cohere API pricing and OpenAI API pricing, quoted per million tokens. Official rate sheets: https://anotherwrapper.com/tools/llm-pricing and https://developers.openai.com/api/docs/pricing. Prompt caching, batch APIs, and committed-use discounts can change the invoice. Benchmark scores are from official publications and independent evals, updated as new numbers land.

    What is the output token limit for Command A+ and GPT-5 Codex?

    Command A+ supports up to an unspecified number of output tokens per request, while GPT-5 Codex supports up to an unspecified number of output tokens. Output tokens are usually the expensive half of API pricing, so a higher max output cap is a capability, not a discount.

    Which model has better throughput, Command A+ or GPT-5 Codex?

    Neither Command A+ nor GPT-5 Codex has published throughput data on this page yet. Throughput (tokens per second) and time-to-first-token are why two models with the same per-million-token price can still feel different in chat and agents.

    How do I switch the models in this Command A+ vs GPT-5 Codex comparison?

    Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open Command A+ or GPT-5 Codex from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.

    Command A+ vs GPT-5 Codex pricing

    This comparison covers API pricing, context window, throughput, and benchmark scores. Command A+ costs $2.50/M input and $10.00/M output. GPT-5 Codex costs $1.25/M input and $10.00/M output.

    Rank both on the LLM leaderboard, SWE-bench, and Humanity's Last Exam.

    The index

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