Standard Compute
Model comparison 2026

Beam 1.0 vs GPT-5.4

Beam 1.0
Reflection · Balanced · Open weights
$1.60/1M · 1.0M ctx
GPT-5.4
OpenAI · Balanced · Proprietary
$6.25/1M · 1.1M ctx

Community vote

Pick a winner in each dimension. You can change your vote any time.

Output Quality

Correctness and depth of what it produces

Agentic Ability

Tool calls, instruction-following, and multi-step tasks

Speed

Tokens per second and time-to-first-token

Value for Money

How much capability you get per dollar

Reliability

Consistent results: fewer refusals, loops and format breaks

Specs and pricing side by side

Spec
Beam 1.0
GPT-5.4
Maker
Reflection
OpenAI
Blended price / 1M
$1.60
$6.25
Input / output
$1.00 in · $3.00 out / 1M tokens
$2.50 in · $15 out / 1M tokens
Context window
1.0M
1.1M
Open weights
Yes
No
Tool use
Yes
Yes
Reasoning
Yes
Yes
Output Quality
7.0
7.7
Agentic Ability
5.0
6.2
Speed
7.0
7.6
Value for Money
5.7
4.6
Reliability
8.0
8.6

Pricing and capabilities synced from the OpenRouter catalogue. Scores are editorial (0–10).

Verdict: Beam 1.0 or GPT-5.4?

Updated 2026-10-17

Choose Beam 1.0 if you want trying a permissively licensed open-weight coding model through OpenRouter, or self-hosting it where code must stay on your own hardware. Choose GPT-5.4 if you want existing GPT-5.4 setups that have not moved to the GPT-6 family.

In our editorial scoring, GPT-5.4 leads in 4 of five dimensions (output quality, agentic ability, speed and reliability), while Beam 1.0 leads in 1. On price, Beam 1.0 runs about $1.60 per 1M tokens (blended) and is open-weight; GPT-5.4 is about $6.25 and proprietary.

Where Beam 1.0 falls short
  • Every published benchmark figure is Reflection's own so far
  • Text only: no image input
Full Beam 1.0 breakdown →
Where GPT-5.4 falls short
  • Superseded by the GPT-6 family; GPT-6.1 Sol scores higher for less
  • Prompts over 272K tokens bill at higher rates
Full GPT-5.4 breakdown →

The agent matters as much as the model. Compare AI agents →

Current Claude, GPT, Gemini and open models run on Standard Compute

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