DeepSeek V4 Pro vs GLM-5.3
GLM-5.3 leads on coding; reasoning and tool use are statistical ties; DeepSeek V4 Pro is cheaper per million tokens.
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As of 26 Oct 2026, 11:37 UTC · 24-hour board
- 90
- DeepSeek V4 Pro on the Combined board, last 24 hours · joint 1st of 24
- 91
- GLM-5.3 on the Combined board, last 24 hours · joint 1st of 24
- 1.1×
- price gap per token: GLM-5.3 lists at $1.40 in / $4.40 out per 1M tokens, DeepSeek V4 Pro at $1.32 in / $3.96 out
01
DeepSeek V4 Pro vs GLM-5.3 at a glance
Both models on the same four boards, the same list-price view and the same drift detectors. Scores carry their standard error; a place is shared, written joint, when the gap is inside that noise.
| Measure | DeepSeek V4 Pro | GLM-5.3 |
|---|---|---|
| Combinedscore ± standard error · place, 24-hour board | 90 ± 2.2joint 1st of 24 | 91 ± 2.2joint 1st of 24 |
| Codingscore ± standard error · place, 24-hour board | 87 ± 0.3joint 18th of 24 | 90 ± 0.2joint 16th of 24 |
| Reasoningscore ± standard error · place, 24-hour board | 95 ± 2.5joint 1st of 22 | 91 ± 2.5joint 15th of 22 |
| Tool usescore ± standard error · place, 24-hour board | 91 ± 2.5joint 1st of 22 | 91 ± 2.5joint 1st of 22 |
| List price per 1M tokensinput / output · blended 40/60 | $1.32 / $3.96$2.90 blended | $1.40 / $4.40$3.20 blended |
| Median response timecoding tasks, last 30 days | 11 s | 12 s |
| Pass ratecoding attempts, last 30 days | 82% | 83% |
| Cost per 1,000 correct answerscoding, last 30 days, every attempt billed | $3.19 | $3.22 |
| Drift statustrend on the 24-hour board · Page-Hinkley per suite | Holding steadyno detection on coding, reasoning and tool use | Holding steadyno detection on coding, reasoning and tool use |
| Tracked since | 17 May 2026161 days | 23 Sep 202632 days |
The boards re-rank after every run, so the figures here follow the leaderboard: each model’s own page, DeepSeek V4 Pro and GLM-5.3, carry the full history. The whole board for each category is on best LLM for coding, best LLM for reasoning and best AI model for agents.
02
Is DeepSeek V4 Pro better than GLM-5.3 for coding?
The Coding board: seven repository debugging tasks graded by running the project’s own tests, including hidden tests the model never sees, re-tested every four hours.
DeepSeek V4 Pro scores 87 ± 0.3 — joint 18th of the 24 models on the Coding board in the last 24 hours. GLM-5.3 scores 90 ± 0.2 — joint 16th of the 24 models on the Coding board in the last 24 hours. The gap of 3 points is beyond the measurement noise, so GLM-5.3 leads on coding.
Over the last 30 days, DeepSeek V4 Pro passed 82% of its coding attempts and GLM-5.3 83%.
See every model on the Coding board on best LLM for coding, or each model’s own page, DeepSeek V4 Pro and GLM-5.3.
03
Is DeepSeek V4 Pro better than GLM-5.3 for reasoning?
The Reasoning board: four long, multi-turn working sessions every day, with continuity checked by running code against rules stated earlier in the session.
DeepSeek V4 Pro scores 95 ± 2.5 — joint 1st of the 22 models on the Reasoning board in the last 24 hours. GLM-5.3 scores 91 ± 2.5 — joint 15th of the 22 models on the Reasoning board in the last 24 hours. The gap of 4 points is within the measurement noise, so head to head the two are a statistical tie on reasoning; the board places them apart because a place is set against the leader of the group above, not against the other model.
See every model on the Reasoning board on best LLM for reasoning.
04
Is DeepSeek V4 Pro or GLM-5.3 better for agents and tool calling?
The Tool use board: nine tasks, each in a real sandboxed machine — either the job is done at the end or it is not. Task completion, tool selection, parameter accuracy, efficiency, error handling, context awareness and safety are scored.
DeepSeek V4 Pro scores 91 ± 2.5 — joint 1st of the 22 models on the Tool use board in the last 24 hours. GLM-5.3 scores 91 ± 2.5 — joint 1st of the 22 models on the Tool use board in the last 24 hours. They score the same: a statistical tie on tool use.
See every model on the Tool use board on best AI model for agents.
05
Which is cheaper, DeepSeek V4 Pro or GLM-5.3?
List prices are each provider’s standard rate per million tokens, cache-miss input and output. Cost per correct answer counts every attempt on the coding tasks, failed ones included, over the last 30 days.
DeepSeek V4 Pro lists at $1.32 in / $3.96 out per 1M tokens; GLM-5.3 at $1.40 in / $4.40 out.
On a 40/60 input–output blend, GLM-5.3 costs about 1.1× as much per token as DeepSeek V4 Pro.
Over the last 30 days, 1,000 correct coding answers cost about $3.19 with DeepSeek V4 Pro and $3.22 with GLM-5.3, every attempt billed, failed ones included.
The cheapest model that still passes the tests is on best value AI model.
06
Which is faster, DeepSeek V4 Pro or GLM-5.3?
Median response time of one attempt or one session, from the same runs as the scores, over the last 30 days.
Median response time on the coding tasks over the last 30 days: DeepSeek V4 Pro 11 s, GLM-5.3 12 s.
The two are close.
On the reasoning sessions 2.1 min against 2.0 min and on the tool-use sessions 1.2 min against 1.8 min (DeepSeek V4 Pro first).
Every model’s median is on fastest AI model.
07
Is DeepSeek V4 Pro or GLM-5.3 getting worse?
Page-Hinkley change-point detection (a CUSUM-family test) runs per suite on each model’s daily median, with every constant published; a real shift is confirmed over days, not hours. An hourly canary of two fixed coding probes catches sharp drops.
DeepSeek V4 Pro is holding steady on the 24-hour board; no Page-Hinkley detection on coding, reasoning or tool use.
GLM-5.3 is holding steady on the 24-hour board; no Page-Hinkley detection on coding, reasoning or tool use.
The family pages answer the question for every model of a provider: Is DeepSeek getting worse? and Are AI models getting worse?. The method is on AI drift detection.
Three models free · email when a watched model's coding score falls five points in a week
Three models free · email when a watched model's coding score falls five points in a week
08
Should I use DeepSeek V4 Pro or GLM-5.3?
Only a difference that clears a threshold counts: a board lead beyond the measurement noise (the leaderboard’s own tie rule), 10% on list price, 20% on response time or cost per correct answer.
Choose DeepSeek V4 Pro when
- price per token matters: it lists at $1.32 in / $3.96 out per 1M tokens against $1.40 in / $4.40 out
Choose GLM-5.3 when
- the work is coding: it leads the Coding board by 3 points in the last 24 hours (90 ± 0.2 against 87 ± 0.3)
09
Can I route between DeepSeek V4 Pro and GLM-5.3 automatically?
One OpenAI-compatible endpoint sends each request to whichever model the boards favour for that kind of work, with your own provider keys.
Yes. The Smart Router is one OpenAI-compatible endpoint with 14 auto-* routing modes: a quality mode such as auto-coding sends each request to the model placing highest on that board, the value modes pick within 5 points of the best and then the cheapest measured cost per run, and auto-split sends traffic by weights you set. Routing is drift-aware by default, uses your own provider keys and adds zero markup on tokens. Free includes 1,000 routed requests a month.
Every mode is described in the router documentation.
1,000 routed requests a month free · your own provider keys · no card
10
How we test DeepSeek V4 Pro and GLM-5.3
Every model on the board runs the same tasks on the same schedule: coding every four hours, reasoning and tool use daily, with an hourly canary probe.
Scores come from our own runs through each provider’s public API, not vendor-reported numbers. Every model gets the same prompts and output budget, and the same sampling settings wherever a provider accepts them, and is graded by executing what it produces. Every score carries a standard error from its own run-to-run repeatability; models whose lead is inside that noise share a place, written joint.
The methodology is public — every weight, statistical test and drift constant. The test tasks are private, so no lab can train on them. The full method, weights and constants are on the methodology page.
11
DeepSeek V4 Pro vs GLM-5.3: questions people ask
Is DeepSeek V4 Pro better than GLM-5.3 for coding?
DeepSeek V4 Pro scores 87 ± 0.3 — joint 18th of the 24 models on the Coding board in the last 24 hours. GLM-5.3 scores 90 ± 0.2 — joint 16th of the 24 models on the Coding board in the last 24 hours. The gap of 3 points is beyond the measurement noise, so GLM-5.3 leads on coding. Over the last 30 days, DeepSeek V4 Pro passed 82% of its coding attempts and GLM-5.3 83%.
Is DeepSeek V4 Pro better than GLM-5.3 for reasoning?
DeepSeek V4 Pro scores 95 ± 2.5 — joint 1st of the 22 models on the Reasoning board in the last 24 hours. GLM-5.3 scores 91 ± 2.5 — joint 15th of the 22 models on the Reasoning board in the last 24 hours. The gap of 4 points is within the measurement noise, so head to head the two are a statistical tie on reasoning; the board places them apart because a place is set against the leader of the group above, not against the other model.
Is DeepSeek V4 Pro or GLM-5.3 better for agents and tool calling?
DeepSeek V4 Pro scores 91 ± 2.5 — joint 1st of the 22 models on the Tool use board in the last 24 hours. GLM-5.3 scores 91 ± 2.5 — joint 1st of the 22 models on the Tool use board in the last 24 hours. They score the same: a statistical tie on tool use.
Which is cheaper, DeepSeek V4 Pro or GLM-5.3?
DeepSeek V4 Pro lists at $1.32 in / $3.96 out per 1M tokens; GLM-5.3 at $1.40 in / $4.40 out. On a 40/60 input–output blend, GLM-5.3 costs about 1.1× as much per token as DeepSeek V4 Pro. Over the last 30 days, 1,000 correct coding answers cost about $3.19 with DeepSeek V4 Pro and $3.22 with GLM-5.3, every attempt billed, failed ones included.
Which is faster, DeepSeek V4 Pro or GLM-5.3?
Median response time on the coding tasks over the last 30 days: DeepSeek V4 Pro 11 s, GLM-5.3 12 s. The two are close. On the reasoning sessions 2.1 min against 2.0 min and on the tool-use sessions 1.2 min against 1.8 min (DeepSeek V4 Pro first).
Is DeepSeek V4 Pro or GLM-5.3 getting worse?
DeepSeek V4 Pro is holding steady on the 24-hour board; no Page-Hinkley detection on coding, reasoning or tool use. GLM-5.3 is holding steady on the 24-hour board; no Page-Hinkley detection on coding, reasoning or tool use. Page-Hinkley change-point detection (a CUSUM-family test) runs per suite on each model’s daily median, with every constant published; a real shift is confirmed over days, not hours. An hourly canary of two fixed coding probes catches sharp drops.
Should I use DeepSeek V4 Pro or GLM-5.3?
GLM-5.3 leads on coding; reasoning and tool use are statistical ties; DeepSeek V4 Pro is cheaper per million tokens. Choose DeepSeek V4 Pro when price per token matters: it lists at $1.32 in / $3.96 out per 1M tokens against $1.40 in / $4.40 out. Choose GLM-5.3 when the work is coding: it leads the Coding board by 3 points in the last 24 hours (90 ± 0.2 against 87 ± 0.3).
Can I route between DeepSeek V4 Pro and GLM-5.3 automatically?
Yes. The Smart Router is one OpenAI-compatible endpoint with 14 auto-* routing modes: a quality mode such as auto-coding sends each request to the model placing highest on that board, the value modes pick within 5 points of the best and then the cheapest measured cost per run, and auto-split sends traffic by weights you set. Routing is drift-aware by default, uses your own provider keys and adds zero markup on tokens. Free includes 1,000 routed requests a month.
Route between them automatically
The Smart Router sends each request to whichever of DeepSeek V4 Pro and GLM-5.3 — or any model on the board — the boards favour for that kind of work, with your own provider keys and zero markup on tokens.
1,000 routed requests a month free · your own provider keys · no card
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