Zai Org Glm 4.5 Air vs Zai Org Glm 4.6v
Zai Org Glm 4.5 Air (Novita AI, 131,072-token context) versus Zai Org Glm 4.6v (Novita AI, 131,072-token context). Zai Org Glm 4.5 Air is cheaper by 18% on a blended token mix. Zai Org Glm 4.6v uniquely supports vision input and structured output (json schema). Use the live calculator below to plug your real usage shape into both, then route the winner via Agent Command Center for shadow A/B without code changes.
Bottom line — Zai Org Glm 4.5 Air vs Zai Org Glm 4.6v
Zai Org Glm 4.5 Air and Zai Org Glm 4.6v target overlapping workloads but differ sharply on economics. Zai Org Glm 4.5 Air runs roughly 18% cheaper on a blended input-plus-output token mix, which translates to approximately $540 per month at mid-market volume (100K requests/day). The gap compounds at enterprise scale, making the cost axis the first filter most teams apply when deciding between these two models.
On capability surface area, the models diverge: Zai Org Glm 4.6v supports vision input where the other does not; Zai Org Glm 4.6v supports structured output (json schema) where the other does not. These differences are binary — either your workload needs the capability or it does not. Check whether any critical path in your agent pipeline depends on a capability only one model provides before committing to a migration.
For teams evaluating both models, the recommended path is a shadow A/B test: route production traffic through an OpenAI-compatible gateway, mirror a percentage to the candidate model, score both responses with an automated evaluator (faithfulness, tool-call correctness, latency), and compare cohort-level metrics over two weeks. Future AGI Agent Command Center supports this pattern with a single `base_url` change and built-in evaluators from the ai-evaluation SDK.
Live workload comparison
Same workload run through both models. The cheaper one is highlighted.
strategy: cost-optimized
primary:
model: zai-org-glm-4-5-air
provider: novita-ai
fallback:
model: zai-org-glm-4-6v
provider: novita-ai
shadow: { sample_rate: 0.05 } # mirror 5% of traffic to compare quality live| Zai Org Glm 4.5 Air | Zai Org Glm 4.6v | |
|---|---|---|
| Input price | $0.130/M | $0.300/M |
| Output price | $0.850/M | $0.900/M |
| Context window | 131,072 | 131,072 |
| Max output | 98,304 | 32,768 |
| Function calling | ✓ | ✓ |
| Vision | — | ✓ |
| Audio input | — | — |
| Reasoning | ✓ | ✓ |
| Prompt caching | — | — |
| Structured output | — | ✓ |
| Pricing verified | Jun 2, 2026 | Jun 2, 2026 |
Cost at scale: monthly spend at three usage volumes
Estimated monthly cost assuming 1,000 input + 200 output tokens per request — a realistic chat-agent shape. Adjust your own usage in the calculator at the top of this page for an exact number.
| Scale | Zai Org Glm 4.5 Air | Zai Org Glm 4.6v | Delta |
|---|---|---|---|
| Startup 10K requests/day | $90.00 /mo | $144 /mo | $54.00/mo |
| Mid-market 100K requests/day | $900 /mo | $1,440 /mo | $540/mo |
| Enterprise 1M requests/day | $9,000 /mo | $14,400 /mo | $5,400/mo |
At enterprise scale (1M requests/day), a difference of even ~10% in unit price compounds into thousands of dollars per month. Cached input pricing and batch tiers can shift this further — both are surfaced on each model's own page.
When to choose which
Picked from the data above — not vendor marketing. Match the rules to your workload, not the other way around.
You're cost-sensitive at scale — Zai Org Glm 4.5 Air runs ~18% cheaper on a blended in+out token mix, compounding into thousands of dollars per month at production volume.
Your inputs include screenshots, diagrams, or product photos — Zai Org Glm 4.6v accepts image input natively, the other doesn't.
Capability diff — what you gain and lose on the swap
A specific list of what each model has that the other doesn't. If your workload depends on a row in Only Zai Org Glm 4.5 Air, switching to Zai Org Glm 4.6v means re-architecting that path (and vice versa).
- • Vision input
- • Structured output (JSON schema)
Capabilities both share (4)
- ✓ Function calling
- ✓ Parallel tool calls
- ✓ Streaming
- ✓ Native reasoning mode
Migration considerations
Concrete differences to wire through your stack before you flip traffic from one to the other.
- Max output tokens differ: 98,304 on Zai Org Glm 4.5 Air vs 32,768 on Zai Org Glm 4.6v. Long-form generation tasks may truncate differently — adjust streaming UI and chunking accordingly.
- Zai Org Glm 4.6v has capabilities Zai Org Glm 4.5 Air lacks: Vision input, Structured output (JSON schema). Worth wiring through the agent design before commit.
How to A/B test Zai Org Glm 4.5 Air vs Zai Org Glm 4.6v in production
If you're stuck between the two, run them side-by-side on real traffic. Four steps the Future AGI team uses internally:
- 1. Point your existing OpenAI SDK at
https://gateway.futureagi.com/v1. No code change beyondbase_urland a virtual key. - 2. Mark Zai Org Glm 4.5 Air primary, mirror 20% of traffic to Zai Org Glm 4.6v in shadow mode. Both responses are logged; only the primary is served to users.
- 3. Score every shadow response with an evaluator — faithfulness, tool-call correctness, response latency, cost. Built-in evaluators in ai-evaluation cover the common axes.
- 4. Compare cohort-level metrics after two weeks. Switch primary when the candidate wins on what matters to your workload — and stays within your latency budget.
Full walkthrough on the Agent Command Center page.
FAQ — Zai Org Glm 4.5 Air vs Zai Org Glm 4.6v
Which is cheaper, Zai Org Glm 4.5 Air or Zai Org Glm 4.6v? ▾
Zai Org Glm 4.5 Air is cheaper by roughly 18% on a blended input + output token mix. Input prices are $0.130/M for Zai Org Glm 4.5 Air versus $0.300/M for Zai Org Glm 4.6v; output prices are $0.850/M versus $0.900/M. The exact savings depend on your input:output ratio — use the live calculator above to plug in your own request shape.
What is the context window of Zai Org Glm 4.5 Air versus Zai Org Glm 4.6v? ▾
Zai Org Glm 4.5 Air supports up to 131,072 tokens of context. Zai Org Glm 4.6v supports up to 131,072 tokens. Zai Org Glm 4.6v has the larger window by a factor of 1.0x, which matters for long-document RAG, multi-turn agent sessions, and tasks that need to keep an entire codebase in working memory.
Do Zai Org Glm 4.5 Air and Zai Org Glm 4.6v both support tool calling? ▾
Yes — both Zai Org Glm 4.5 Air and Zai Org Glm 4.6v support native function calling. Both also support structured output via JSON schema, so an agent can be ported between them with the same tool definitions.
Can Zai Org Glm 4.5 Air and Zai Org Glm 4.6v process images? ▾
Zai Org Glm 4.6v accepts native image input. Zai Org Glm 4.5 Air does not — you would need to route image-heavy workloads through Zai Org Glm 4.6v or add a separate vision model in front of Zai Org Glm 4.5 Air.
When should I choose Zai Org Glm 4.5 Air over Zai Org Glm 4.6v? ▾
You're cost-sensitive at scale — Zai Org Glm 4.5 Air runs ~18% cheaper on a blended in+out token mix, compounding into thousands of dollars per month at production volume.
When should I choose Zai Org Glm 4.6v over Zai Org Glm 4.5 Air? ▾
Your inputs include screenshots, diagrams, or product photos — Zai Org Glm 4.6v accepts image input natively, the other doesn't.
How do I A/B test Zai Org Glm 4.5 Air against Zai Org Glm 4.6v in production? ▾
Route both through an OpenAI-compatible gateway like Future AGI Agent Command Center with shadow mode enabled. Send 100% of traffic to your primary model, mirror 10–20% to the candidate, score every response with an evaluator (faithfulness, tool-call correctness, response time), and compare cohort-level metrics for two weeks. Switch when the candidate wins on the metrics that matter to your workload and stays within your latency budget.