Accounts Fireworks Models Glm 4p6 vs Accounts Fireworks Models Glm 4p7
Accounts Fireworks Models Glm 4p6 (Fireworks AI, 202,800-token context) versus Accounts Fireworks Models Glm 4p7 (Fireworks AI, 202,800-token context). Accounts Fireworks Models Glm 4p6 is cheaper by 2% on a blended token mix. 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 — Accounts Fireworks Models Glm 4p6 vs Accounts Fireworks Models Glm 4p7
Accounts Fireworks Models Glm 4p6 and Accounts Fireworks Models Glm 4p7 are priced within 2% of each other, so cost alone is not the deciding factor. The comparison comes down to capabilities, context window, and benchmark performance on the specific task shape your workload demands.
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: accounts-fireworks-models-glm-4p6
provider: fireworks-ai
fallback:
model: accounts-fireworks-models-glm-4p7
provider: fireworks-ai
shadow: { sample_rate: 0.05 } # mirror 5% of traffic to compare quality live| Accounts Fireworks Models Glm 4p6 | Accounts Fireworks Models Glm 4p7 | |
|---|---|---|
| Input price | $0.550/M | $0.600/M |
| Output price | $2.19/M | $2.20/M |
| Context window | 202,800 | 202,800 |
| Max output | 202,800 | 202,800 |
| 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 | Accounts Fireworks Models Glm 4p6 | Accounts Fireworks Models Glm 4p7 | Delta |
|---|---|---|---|
| Startup 10K requests/day | $296 /mo | $312 /mo | $15.60/mo |
| Mid-market 100K requests/day | $2,964 /mo | $3,120 /mo | $156/mo |
| Enterprise 1M requests/day | $29,640 /mo | $31,200 /mo | $1,560/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.
How to A/B test Accounts Fireworks Models Glm 4p6 vs Accounts Fireworks Models Glm 4p7 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 Accounts Fireworks Models Glm 4p6 primary, mirror 20% of traffic to Accounts Fireworks Models Glm 4p7 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 — Accounts Fireworks Models Glm 4p6 vs Accounts Fireworks Models Glm 4p7
Which is cheaper, Accounts Fireworks Models Glm 4p6 or Accounts Fireworks Models Glm 4p7? ▾
Accounts Fireworks Models Glm 4p6 is cheaper by roughly 2% on a blended input + output token mix. Input prices are $0.550/M for Accounts Fireworks Models Glm 4p6 versus $0.600/M for Accounts Fireworks Models Glm 4p7; output prices are $2.19/M versus $2.20/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 Accounts Fireworks Models Glm 4p6 versus Accounts Fireworks Models Glm 4p7? ▾
Accounts Fireworks Models Glm 4p6 supports up to 202,800 tokens of context. Accounts Fireworks Models Glm 4p7 supports up to 202,800 tokens. Accounts Fireworks Models Glm 4p7 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 Accounts Fireworks Models Glm 4p6 and Accounts Fireworks Models Glm 4p7 both support tool calling? ▾
Yes — both Accounts Fireworks Models Glm 4p6 and Accounts Fireworks Models Glm 4p7 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.
How do I A/B test Accounts Fireworks Models Glm 4p6 against Accounts Fireworks Models Glm 4p7 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.